diff --git a/.gitignore b/.gitignore
index a5c63f9..ae355cb 100644
--- a/.gitignore
+++ b/.gitignore
@@ -198,5 +198,4 @@ venv.bak/
 .mypy_cache/
 
 grpc/tmp.jpg
-Dockerfile
 run_prod.sh
diff --git a/.idea/bl-detect.iml b/.idea/bl-detect.iml
index 6f51965..b8fe1f4 100644
--- a/.idea/bl-detect.iml
+++ b/.idea/bl-detect.iml
@@ -1,9 +1,13 @@
 <?xml version="1.0" encoding="UTF-8"?>
 <module type="PYTHON_MODULE" version="4">
   <component name="NewModuleRootManager">
-    <content url="file://$MODULE_DIR$" />
-    <orderEntry type="jdk" jdkName="Python 3.6.2 (~/anaconda/envs/bl-detect/bin/python)" jdkType="Python SDK" />
+    <content url="file://$MODULE_DIR$">
+      <excludeFolder url="file://$MODULE_DIR$/stylelens" />
+    </content>
+    <orderEntry type="jdk" jdkName="Python 3.6 (bl-detect)" jdkType="Python SDK" />
     <orderEntry type="sourceFolder" forTests="false" />
+    <orderEntry type="library" name="R User Library" level="project" />
+    <orderEntry type="library" name="R Skeletons" level="application" />
   </component>
   <component name="TestRunnerService">
     <option name="PROJECT_TEST_RUNNER" value="Unittests" />
diff --git a/.idea/inspectionProfiles/Project_Default.xml b/.idea/inspectionProfiles/Project_Default.xml
new file mode 100644
index 0000000..86fdf70
--- /dev/null
+++ b/.idea/inspectionProfiles/Project_Default.xml
@@ -0,0 +1,25 @@
+<component name="InspectionProjectProfileManager">
+  <profile version="1.0">
+    <option name="myName" value="Project Default" />
+    <inspection_tool class="PyCompatibilityInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ourVersions">
+        <value>
+          <list size="2">
+            <item index="0" class="java.lang.String" itemvalue="2.7" />
+            <item index="1" class="java.lang.String" itemvalue="3.6" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+    <inspection_tool class="PyPackageRequirementsInspection" enabled="true" level="WARNING" enabled_by_default="true">
+      <option name="ignoredPackages">
+        <value>
+          <list size="2">
+            <item index="0" class="java.lang.String" itemvalue="stylelens-feature" />
+            <item index="1" class="java.lang.String" itemvalue="tensorflow-gpu" />
+          </list>
+        </value>
+      </option>
+    </inspection_tool>
+  </profile>
+</component>
\ No newline at end of file
diff --git a/.idea/misc.xml b/.idea/misc.xml
index 14537a1..89ed053 100644
--- a/.idea/misc.xml
+++ b/.idea/misc.xml
@@ -3,5 +3,8 @@
   <component name="PreferredVcsStorage">
     <preferredVcsName>ApexVCS</preferredVcsName>
   </component>
-  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.6.2 (~/anaconda/envs/bl-detect/bin/python)" project-jdk-type="Python SDK" />
+  <component name="ProjectRootManager" version="2" project-jdk-name="Python 3.6 (bl-detect)" project-jdk-type="Python SDK" />
+  <component name="PythonCompatibilityInspectionAdvertiser">
+    <option name="version" value="2" />
+  </component>
 </project>
\ No newline at end of file
diff --git a/Dockerfile b/Dockerfile
new file mode 100644
index 0000000..45fc416
--- /dev/null
+++ b/Dockerfile
@@ -0,0 +1,15 @@
+FROM bluelens/tensorflow:latest-gpu-py3
+
+
+RUN mkdir /usr/src/app
+WORKDIR /usr/src/app
+
+COPY . /usr/src/app
+
+#RUN curl https://storage.googleapis.com/tensorflow/linux/gpu/tensorflow_gpu-0.12.1-cp35-cp35m-linux_x86_64.whl -o ./tensorflow_gpu-0.12.1-cp35-cp35m-linux_x86_64.whl
+#RUN pip3 install tensorflow_gpu-0.12.1-cp35-cp35m-linux_x86_64.whl
+RUN pip install --no-cache-dir -r requirements.txt
+
+ENV PYTHONPATH $PYTHONPATH:/usr/src/app
+
+CMD ["python", "grpc/object_detect_server.py"]
diff --git a/grpc/feature_extract.py b/grpc/feature_extract.py
deleted file mode 100755
index 7afc78c..0000000
--- a/grpc/feature_extract.py
+++ /dev/null
@@ -1,39 +0,0 @@
-# coding: utf-8
-"""
-    stylelens-feature
-
-    This is a API document for Object Detection on fashion items\"
-
-    OpenAPI spec version: 0.0.1
-    Contact: devops@bluehack.net
-    Generated by: https://github.com/swagger-api/swagger-codegen.git
-"""
-
-from __future__ import absolute_import
-
-import numpy as np
-import os
-import tensorflow as tf
-
-class ExtractFeature(object):
-  def __init__(self):
-    try:
-      MODEL = os.environ['CLASSIFY_GRAPH']
-    except:
-      print("!!! Need to define environment variable: CLASSIFY_GRAPH=/path/to/model.pb")
-
-    with tf.gfile.FastGFile(MODEL, 'rb') as f:
-      graph_def = tf.GraphDef()
-      graph_def.ParseFromString(f.read())
-      _ = tf.import_graph_def(graph_def, name='')
-
-    with tf.Session() as self.sess:
-      self.pool3 = self.sess.graph.get_tensor_by_name('pool_3:0')
-
-  def extract_feature(self, file):
-    with tf.gfile.GFile(file, 'rb') as fid:
-      image_data = fid.read()
-      pool3_features = self.sess.run(self.pool3,{'DecodeJpeg/contents:0': image_data})
-      feature = np.squeeze(pool3_features)
-      return feature.tobytes()
-
diff --git a/grpc/object_detect_all.py b/grpc/object_detect_all.py
deleted file mode 100755
index 8d8c3ec..0000000
--- a/grpc/object_detect_all.py
+++ /dev/null
@@ -1,213 +0,0 @@
-# coding: utf-8
-
-from __future__ import absolute_import
-
-import numpy as np
-import os
-from util import s3
-from PIL import Image
-import tensorflow as tf
-from object_detection.utils import visualization_utils as vis_util
-from stylelens_feature.feature_extract import ExtractFeature
-from bluelens_log import Logging
-
-import io
-from util import label_map_util
-
-TMP_CROP_IMG_FILE = './tmp.jpg'
-
-NUM_CLASSES = 3
-
-AWS_BUCKET = 'bluelens-style-model'
-AWS_BUCKET_FOLDER = 'object_detection'
-MODEL_TYPE = '3class'
-AWS_ACCESS_KEY = os.environ['AWS_ACCESS_KEY']
-AWS_SECRET_ACCESS_KEY = os.environ['AWS_SECRET_ACCESS_KEY']
-REDIS_SERVER = os.environ['REDIS_SERVER']
-REDIS_PASSWORD = os.environ['REDIS_PASSWORD']
-RELEASE_MODE = os.environ['RELEASE_MODE']
-FEATURE_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-FEATURE_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-OD_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_SCORE_MIN = float(os.environ['OD_SCORE_MIN'])
-GPU_NUM = os.environ['GPU_NUM']
-GPU = '/device:GPU:' + GPU_NUM
-
-MODEL_FILE = 'frozen_inference_graph.pb'
-LABEL_MAP_FILE = 'label_map.pbtxt'
-options = {
-  'REDIS_SERVER': REDIS_SERVER,
-  'REDIS_PASSWORD': REDIS_PASSWORD
-}
-log = Logging(options, tag='bl-detect:AllObjectDetect')
-storage = s3.S3(AWS_ACCESS_KEY, AWS_SECRET_ACCESS_KEY)
-
-class AllObjectDetect(object):
-  def __init__(self):
-    label_map_file = self.load_labelemap()
-    label_map = label_map_util.load_labelmap(label_map_file)
-    log.debug(label_map)
-    categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES,
-                                                                use_display_name=True)
-    self.__category_index = label_map_util.create_category_index(categories)
-    self.__detection_graph = tf.Graph()
-    self.__feature_extractor = ExtractFeature(use_gpu=True)
-    model_file = self.load_model()
-    with self.__detection_graph.as_default():
-      od_graph_def = tf.GraphDef()
-      with tf.gfile.GFile(model_file, 'rb') as fid:
-        serialized_graph = fid.read()
-        od_graph_def.ParseFromString(serialized_graph)
-        tf.import_graph_def(od_graph_def, name='')
-
-      with tf.device(GPU):
-        config = tf.ConfigProto()
-        config.gpu_options.allow_growth = True
-        self.__sess = tf.Session(config=config, graph=self.__detection_graph)
-
-    log.info('_init_ done')
-
-  def load_labelemap(self):
-    log.info('load_labelmap')
-    file = os.path.join(os.getcwd(), LABEL_MAP_FILE)
-    key = os.path.join(AWS_BUCKET_FOLDER, RELEASE_MODE, MODEL_TYPE, LABEL_MAP_FILE)
-    print(key)
-    try:
-      return storage.download_file_from_bucket(AWS_BUCKET, file, key)
-    except:
-      log.error('download error')
-      return None
-
-  def load_model(self):
-    log.info('load_model')
-    file = os.path.join(os.getcwd(), MODEL_FILE)
-    key = os.path.join(AWS_BUCKET_FOLDER, RELEASE_MODE, MODEL_TYPE, MODEL_FILE)
-    print(key)
-    try:
-      return storage.download_file_from_bucket(AWS_BUCKET, file, key)
-    except:
-      log.error('download error')
-      return None
-
-  def detect(self, image_bytes):
-
-    image_data = Image.open(io.BytesIO(image_bytes))
-    image_np = self.load_image_into_numpy_array(image_data)
-
-    show_box = False
-    out_image, boxes, scores, classes, num_detections = self.detect_objects(image_np, self.__sess, self.__detection_graph, show_box)
-
-    out_boxes = self.take_object(
-      out_image,
-      np.squeeze(boxes),
-      np.squeeze(scores),
-      np.squeeze(classes).astype(np.int32))
-
-    # log.debug(out_boxes)
-    return out_boxes
-
-  def take_object(self, image_np, boxes, scores, classes):
-    max_boxes_to_save = 3
-    taken_boxes = []
-    if not max_boxes_to_save:
-      max_boxes_to_save = boxes.shape[0]
-    for i in range(min(max_boxes_to_save, boxes.shape[0])):
-      if scores is None or scores[i] > OD_SCORE_MIN:
-        print(scores[i])
-        if classes[i] in self.__category_index.keys():
-          class_name = self.__category_index[classes[i]]['name']
-          class_code = str(self.__category_index[classes[i]]['id'])
-        else:
-          class_name = 'na'
-          class_code = 'na'
-        ymin, xmin, ymax, xmax = tuple(boxes[i].tolist())
-
-        use_normalized_coordinates = True
-        image_pil = Image.fromarray(np.uint8(image_np)).convert('RGB')
-
-        left, right, top, bottom = self.crop_bounding_box(
-          image_pil,
-          ymin,
-          xmin,
-          ymax,
-          xmax,
-          use_normalized_coordinates=use_normalized_coordinates)
-
-        feature_vector = self.extract_feature(image_pil, left, right, top, bottom)
-        item = {}
-
-        item['box'] = [left, right, top, bottom]
-        item['class_name'] = class_name
-        item['class_code'] = class_code
-        item['score'] = scores[i]
-        item['feature'] = feature_vector
-        taken_boxes.append(item)
-    return taken_boxes
-
-  def extract_feature(self, image, left, right, top, bottom):
-    area = (left, top, left + abs(left-right), top + abs(bottom-top))
-    cropped_img = image.crop(area)
-    cropped_img.save(TMP_CROP_IMG_FILE)
-    # cimage = io.BytesIO()
-    # cropped_img.save(cimage, format='JPEG')
-    # cimage.seek(0)  # rewind to the start
-    # cimage = Image.open(cimage)
-    feature = self.__feature_extractor.extract_feature(TMP_CROP_IMG_FILE)
-    return feature
-
-  def load_image_into_numpy_array(self, image):
-    (im_width, im_height) = image.size
-    return np.array(image.getdata()).reshape(
-      (im_height, im_width, 3)).astype(np.uint8)
-
-  def crop_bounding_box(self,
-                        image,
-                        ymin,
-                        xmin,
-                        ymax,
-                        xmax,
-                        use_normalized_coordinates=True):
-    im_width, im_height = image.size
-    # image.show()
-    if use_normalized_coordinates:
-      (left, right, top, bottom) = (xmin * im_width, xmax * im_width,
-                                    ymin * im_height, ymax * im_height)
-    else:
-      (left, right, top, bottom) = (xmin, xmax, ymin, ymax)
-
-    return left, right, top, bottom
-
-  def detect_objects(self, image_np, sess, detection_graph, show_box=True):
-    # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
-    image_np_expanded = np.expand_dims(image_np, axis=0)
-    image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
-
-    # Each box represents a part of the image where a particular object was detected.
-    boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
-
-    # Each score represent how level of confidence for each of the objects.
-    # Score is shown on the result image, together with the class label.
-    scores = detection_graph.get_tensor_by_name('detection_scores:0')
-    classes = detection_graph.get_tensor_by_name('detection_classes:0')
-    num_detections = detection_graph.get_tensor_by_name('num_detections:0')
-
-    # Actual detection.
-    (boxes, scores, classes, num_detections) = sess.run(
-      [boxes, scores, classes, num_detections],
-      feed_dict={image_tensor: image_np_expanded})
-
-    if show_box:
-      # Visualization of the results of a detection.
-      vis_util.visualize_boxes_and_labels_on_image_array(
-        image_np,
-        np.squeeze(boxes),
-        np.squeeze(classes).astype(np.int32),
-        np.squeeze(scores),
-        self.__category_index,
-        use_normalized_coordinates=True,
-        max_boxes_to_draw=3,
-        min_score_thresh=.05,
-        line_thickness=8)
-    # print(image_np)
-    return image_np, boxes, scores, classes, num_detections
diff --git a/grpc/object_detect_bottom.py b/grpc/object_detect_bottom.py
index ca7341f..930f36d 100755
--- a/grpc/object_detect_bottom.py
+++ b/grpc/object_detect_bottom.py
@@ -8,7 +8,9 @@
 from PIL import Image
 import tensorflow as tf
 from object_detection.utils import visualization_utils as vis_util
-from stylelens_feature.feature_extract import ExtractFeature
+#from stylelens_feature.feature_extract import ExtractFeature
+from stylelens_color import ExtractColor
+from stylelens_color.color_extract import ExtractColor
 from bluelens_log import Logging
 
 import io
@@ -26,10 +28,14 @@
 REDIS_SERVER = os.environ['REDIS_SERVER']
 REDIS_PASSWORD = os.environ['REDIS_PASSWORD']
 RELEASE_MODE = os.environ['RELEASE_MODE']
-FEATURE_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-FEATURE_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-OD_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
+COLOR_GRPC_HOST = os.environ['COLOR_GRPC_HOST']
+cOLOR_GRPC_PORT = os.environ['COLOR_GRPC_PORT']
+OD_GRPC_HOST = os.environ['COLOR_GRPC_HOST']
+OD_GRPC_PORT = os.environ['COLOR_GRPC_PORT']
+#FEATURE_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
+#FEATURE_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
+#OD_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
+#OD_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
 OD_SCORE_MIN = float(os.environ['OD_SCORE_MIN'])
 GPU_NUM = os.environ['GPU_NUM']
 GPU = '/device:GPU:' + GPU_NUM
@@ -52,7 +58,8 @@ def __init__(self):
                                                                 use_display_name=True)
     self.__category_index = label_map_util.create_category_index(categories)
     self.__detection_graph = tf.Graph()
-    self.__feature_extractor = ExtractFeature(use_gpu=True)
+    #self.__feature_extractor = ExtractFeature(use_gpu=True)
+    self.__color_extractor = ExtractColor(use_gpu=True)
     model_file = self.load_model()
     with self.__detection_graph.as_default():
       od_graph_def = tf.GraphDef()
@@ -134,7 +141,10 @@ def take_object(self, image_np, boxes, scores, classes):
           xmax,
           use_normalized_coordinates=use_normalized_coordinates)
 
-        feature_vector = self.extract_feature(image_pil, left, right, top, bottom)
+        #feature_vector = self.extract_feature(image_pil, left, right, top, bottom)
+        color = self.extract_color(image_pil, left, right, top, bottom)
+
+
         item = {}
 
         item['box'] = [left, right, top, bottom]
@@ -142,10 +152,12 @@ def take_object(self, image_np, boxes, scores, classes):
         # item['class_code'] = class_code
         item['class_code'] = '2'
         item['score'] = scores[i]
-        item['feature'] = feature_vector
+        #item['feature'] = feature_vector
+        item['color_code'] = color['class_code']
+        item['color_score'] = color['class_score']
         taken_boxes.append(item)
     return taken_boxes
-
+  """
   def extract_feature(self, image, left, right, top, bottom):
     area = (left, top, left + abs(left-right), top + abs(bottom-top))
     cropped_img = image.crop(area)
@@ -156,6 +168,13 @@ def extract_feature(self, image, left, right, top, bottom):
     # cimage = Image.open(cimage)
     feature = self.__feature_extractor.extract_feature(TMP_CROP_IMG_FILE)
     return feature
+  """
+  def extract_color(self, image, left, right, top, bottom):
+    area = (left, top, left + abs(left-right), top + abs(bottom-top))
+    cropped_img = image.crop(area)
+    cropped_img.save(TMP_CROP_IMG_FILE)
+    color = self.__color_extractor.extract_color(TMP_CROP_IMG_FILE)
+    return color
 
   def load_image_into_numpy_array(self, image):
     (im_width, im_height) = image.size
diff --git a/grpc/object_detect_client.py b/grpc/object_detect_client.py
index 5974076..097ef63 100644
--- a/grpc/object_detect_client.py
+++ b/grpc/object_detect_client.py
@@ -48,7 +48,7 @@ def run():
     print(object.class_name)
     print(object.class_code)
     print(object.location)
-    arr = np.fromstring(object.feature, dtype=np.float32)
+    arr = np.fromstring(object.class_code, dtype=np.float32)
     print(arr)
 
 if __name__ == '__main__':
diff --git a/grpc/object_detect_full.py b/grpc/object_detect_full.py
deleted file mode 100755
index 5b067f0..0000000
--- a/grpc/object_detect_full.py
+++ /dev/null
@@ -1,214 +0,0 @@
-# coding: utf-8
-
-from __future__ import absolute_import
-
-import numpy as np
-import os
-from util import s3
-from PIL import Image
-import tensorflow as tf
-from object_detection.utils import visualization_utils as vis_util
-from stylelens_feature.feature_extract import ExtractFeature
-from bluelens_log import Logging
-
-import io
-from util import label_map_util
-
-TMP_CROP_IMG_FILE = './tmp.jpg'
-
-NUM_CLASSES = 1
-
-AWS_BUCKET = 'bluelens-style-model'
-AWS_BUCKET_FOLDER = 'object_detection'
-MODEL_TYPE = 'full'
-AWS_ACCESS_KEY = os.environ['AWS_ACCESS_KEY']
-AWS_SECRET_ACCESS_KEY = os.environ['AWS_SECRET_ACCESS_KEY']
-REDIS_SERVER = os.environ['REDIS_SERVER']
-REDIS_PASSWORD = os.environ['REDIS_PASSWORD']
-RELEASE_MODE = os.environ['RELEASE_MODE']
-FEATURE_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-FEATURE_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-OD_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_SCORE_MIN = float(os.environ['OD_SCORE_MIN'])
-GPU_NUM = os.environ['GPU_NUM']
-GPU = '/device:GPU:' + GPU_NUM
-
-MODEL_FILE = 'frozen_inference_graph.pb'
-LABEL_MAP_FILE = 'label_map.pbtxt'
-options = {
-  'REDIS_SERVER': REDIS_SERVER,
-  'REDIS_PASSWORD': REDIS_PASSWORD
-}
-log = Logging(options, tag='bl-detect:FullObjectDetect')
-storage = s3.S3(AWS_ACCESS_KEY, AWS_SECRET_ACCESS_KEY)
-
-class FullObjectDetect(object):
-  def __init__(self):
-    label_map_file = self.load_labelemap()
-    label_map = label_map_util.load_labelmap(label_map_file)
-    log.debug(label_map)
-    categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES,
-                                                                use_display_name=True)
-    self.__category_index = label_map_util.create_category_index(categories)
-    self.__detection_graph = tf.Graph()
-    self.__feature_extractor = ExtractFeature(use_gpu=True)
-    model_file = self.load_model()
-    with self.__detection_graph.as_default():
-      od_graph_def = tf.GraphDef()
-      with tf.gfile.GFile(model_file, 'rb') as fid:
-        serialized_graph = fid.read()
-        od_graph_def.ParseFromString(serialized_graph)
-        tf.import_graph_def(od_graph_def, name='')
-
-      with tf.device(GPU):
-        config = tf.ConfigProto()
-        config.gpu_options.allow_growth = True
-        self.__sess = tf.Session(config=config, graph=self.__detection_graph)
-
-    log.info('_init_ done')
-
-  def load_labelemap(self):
-    log.info('load_labelmap')
-    file = os.path.join(os.getcwd(), LABEL_MAP_FILE)
-    key = os.path.join(AWS_BUCKET_FOLDER, RELEASE_MODE, MODEL_TYPE, LABEL_MAP_FILE)
-    print(key)
-    try:
-      return storage.download_file_from_bucket(AWS_BUCKET, file, key)
-    except:
-      log.error('download error')
-      return None
-
-  def load_model(self):
-    log.info('load_model')
-    file = os.path.join(os.getcwd(), MODEL_FILE)
-    key = os.path.join(AWS_BUCKET_FOLDER, RELEASE_MODE, MODEL_TYPE, MODEL_FILE)
-    print(key)
-    try:
-      return storage.download_file_from_bucket(AWS_BUCKET, file, key)
-    except:
-      log.error('download error')
-      return None
-
-  def detect(self, image_bytes):
-
-    image_data = Image.open(io.BytesIO(image_bytes))
-    image_np = self.load_image_into_numpy_array(image_data)
-
-    show_box = False
-    out_image, boxes, scores, classes, num_detections = self.detect_objects(image_np, self.__sess, self.__detection_graph, show_box)
-
-    out_boxes = self.take_object(
-      out_image,
-      np.squeeze(boxes),
-      np.squeeze(scores),
-      np.squeeze(classes).astype(np.int32))
-
-    # log.debug(out_boxes)
-    return out_boxes
-
-  def take_object(self, image_np, boxes, scores, classes):
-    max_boxes_to_save = 3
-    taken_boxes = []
-    if not max_boxes_to_save:
-      max_boxes_to_save = boxes.shape[0]
-    for i in range(min(max_boxes_to_save, boxes.shape[0])):
-      if scores is None or scores[i] > OD_SCORE_MIN:
-        print(scores[i])
-        if classes[i] in self.__category_index.keys():
-          class_name = self.__category_index[classes[i]]['name']
-          class_code = str(self.__category_index[classes[i]]['id'])
-        else:
-          class_name = 'na'
-          class_code = 'na'
-        ymin, xmin, ymax, xmax = tuple(boxes[i].tolist())
-
-        use_normalized_coordinates = True
-        image_pil = Image.fromarray(np.uint8(image_np)).convert('RGB')
-
-        left, right, top, bottom = self.crop_bounding_box(
-          image_pil,
-          ymin,
-          xmin,
-          ymax,
-          xmax,
-          use_normalized_coordinates=use_normalized_coordinates)
-
-        feature_vector = self.extract_feature(image_pil, left, right, top, bottom)
-        item = {}
-
-        item['box'] = [left, right, top, bottom]
-        item['class_name'] = class_name
-        # item['class_code'] = class_code
-        item['class_code'] = '3'
-        item['score'] = scores[i]
-        item['feature'] = feature_vector
-        taken_boxes.append(item)
-    return taken_boxes
-
-  def extract_feature(self, image, left, right, top, bottom):
-    area = (left, top, left + abs(left-right), top + abs(bottom-top))
-    cropped_img = image.crop(area)
-    cropped_img.save(TMP_CROP_IMG_FILE)
-    # cimage = io.BytesIO()
-    # cropped_img.save(cimage, format='JPEG')
-    # cimage.seek(0)  # rewind to the start
-    # cimage = Image.open(cimage)
-    feature = self.__feature_extractor.extract_feature(TMP_CROP_IMG_FILE)
-    return feature
-
-  def load_image_into_numpy_array(self, image):
-    (im_width, im_height) = image.size
-    return np.array(image.getdata()).reshape(
-      (im_height, im_width, 3)).astype(np.uint8)
-
-  def crop_bounding_box(self,
-                        image,
-                        ymin,
-                        xmin,
-                        ymax,
-                        xmax,
-                        use_normalized_coordinates=True):
-    im_width, im_height = image.size
-    # image.show()
-    if use_normalized_coordinates:
-      (left, right, top, bottom) = (xmin * im_width, xmax * im_width,
-                                    ymin * im_height, ymax * im_height)
-    else:
-      (left, right, top, bottom) = (xmin, xmax, ymin, ymax)
-
-    return left, right, top, bottom
-
-  def detect_objects(self, image_np, sess, detection_graph, show_box=True):
-    # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
-    image_np_expanded = np.expand_dims(image_np, axis=0)
-    image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
-
-    # Each box represents a part of the image where a particular object was detected.
-    boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
-
-    # Each score represent how level of confidence for each of the objects.
-    # Score is shown on the result image, together with the class label.
-    scores = detection_graph.get_tensor_by_name('detection_scores:0')
-    classes = detection_graph.get_tensor_by_name('detection_classes:0')
-    num_detections = detection_graph.get_tensor_by_name('num_detections:0')
-
-    # Actual detection.
-    (boxes, scores, classes, num_detections) = sess.run(
-      [boxes, scores, classes, num_detections],
-      feed_dict={image_tensor: image_np_expanded})
-
-    if show_box:
-      # Visualization of the results of a detection.
-      vis_util.visualize_boxes_and_labels_on_image_array(
-        image_np,
-        np.squeeze(boxes),
-        np.squeeze(classes).astype(np.int32),
-        np.squeeze(scores),
-        self.__category_index,
-        use_normalized_coordinates=True,
-        max_boxes_to_draw=3,
-        min_score_thresh=.05,
-        line_thickness=8)
-    # print(image_np)
-    return image_np, boxes, scores, classes, num_detections
diff --git a/grpc/object_detect_pb2.py b/grpc/object_detect_pb2.py
index d3cea83..5e28c1f 100644
--- a/grpc/object_detect_pb2.py
+++ b/grpc/object_detect_pb2.py
@@ -19,7 +19,7 @@
   name='object_detect.proto',
   package='objectdetect',
   syntax='proto3',
-  serialized_pb=_b('\n\x13object_detect.proto\x12\x0cobjectdetect\"D\n\x08Location\x12\x0c\n\x04left\x18\x01 \x01(\x02\x12\r\n\x05right\x18\x02 \x01(\x02\x12\x0b\n\x03top\x18\x03 \x01(\x02\x12\x0e\n\x06\x62ottom\x18\x04 \x01(\x02\"\"\n\rDetectRequest\x12\x11\n\tfile_data\x18\x01 \x01(\x0c\"\x7f\n\x0b\x44\x65tectReply\x12(\n\x08location\x18\x01 \x01(\x0b\x32\x16.objectdetect.Location\x12\x12\n\nclass_name\x18\x02 \x01(\t\x12\x12\n\nclass_code\x18\x03 \x01(\t\x12\r\n\x05score\x18\x04 \x01(\x02\x12\x0f\n\x07\x66\x65\x61ture\x18\x05 \x01(\x0c\x32R\n\x06\x44\x65tect\x12H\n\nGetObjects\x12\x1b.objectdetect.DetectRequest\x1a\x19.objectdetect.DetectReply\"\x00\x30\x01\x42\x31\n\x13io.stylelens.detectB\x11ObjectDetectProtoP\x01\xa2\x02\x04STYLb\x06proto3')
+  serialized_pb=_b('\n\x13object_detect.proto\x12\x0cobjectdetect\"D\n\x08Location\x12\x0c\n\x04left\x18\x01 \x01(\x02\x12\r\n\x05right\x18\x02 \x01(\x02\x12\x0b\n\x03top\x18\x03 \x01(\x02\x12\x0e\n\x06\x62ottom\x18\x04 \x01(\x02\"\"\n\rDetectRequest\x12\x11\n\tfile_data\x18\x01 \x01(\x0c\"\x97\x01\n\x0b\x44\x65tectReply\x12(\n\x08location\x18\x01 \x01(\x0b\x32\x16.objectdetect.Location\x12\x12\n\nclass_name\x18\x02 \x01(\t\x12\x12\n\nclass_code\x18\x03 \x01(\t\x12\r\n\x05score\x18\x04 \x01(\x02\x12\x12\n\ncolor_code\x18\x05 \x01(\t\x12\x13\n\x0b\x63olor_score\x18\x06 \x01(\x02\x32R\n\x06\x44\x65tect\x12H\n\nGetObjects\x12\x1b.objectdetect.DetectRequest\x1a\x19.objectdetect.DetectReply\"\x00\x30\x01\x42\x31\n\x13io.stylelens.detectB\x11ObjectDetectProtoP\x01\xa2\x02\x04STYLb\x06proto3')
 )
 
 
@@ -144,9 +144,16 @@
       is_extension=False, extension_scope=None,
       options=None),
     _descriptor.FieldDescriptor(
-      name='feature', full_name='objectdetect.DetectReply.feature', index=4,
-      number=5, type=12, cpp_type=9, label=1,
-      has_default_value=False, default_value=_b(""),
+      name='color_code', full_name='objectdetect.DetectReply.color_code', index=4,
+      number=5, type=9, cpp_type=9, label=1,
+      has_default_value=False, default_value=_b("").decode('utf-8'),
+      message_type=None, enum_type=None, containing_type=None,
+      is_extension=False, extension_scope=None,
+      options=None),
+    _descriptor.FieldDescriptor(
+      name='color_score', full_name='objectdetect.DetectReply.color_score', index=5,
+      number=6, type=2, cpp_type=6, label=1,
+      has_default_value=False, default_value=float(0),
       message_type=None, enum_type=None, containing_type=None,
       is_extension=False, extension_scope=None,
       options=None),
@@ -162,8 +169,8 @@
   extension_ranges=[],
   oneofs=[
   ],
-  serialized_start=143,
-  serialized_end=270,
+  serialized_start=144,
+  serialized_end=295,
 )
 
 _DETECTREPLY.fields_by_name['location'].message_type = _LOCATION
@@ -203,8 +210,8 @@
   file=DESCRIPTOR,
   index=0,
   options=None,
-  serialized_start=272,
-  serialized_end=354,
+  serialized_start=297,
+  serialized_end=379,
   methods=[
   _descriptor.MethodDescriptor(
     name='GetObjects',
diff --git a/grpc/object_detect_server.py b/grpc/object_detect_server.py
index 3765263..ffe09bc 100644
--- a/grpc/object_detect_server.py
+++ b/grpc/object_detect_server.py
@@ -20,10 +20,10 @@
 
 import grpc
 
-from object_detect_top import TopObjectDetect
+#from object_detect_top import TopObjectDetect
 from object_detect_bottom import BottomObjectDetect
-from object_detect_full import FullObjectDetect
-from object_detect_all import AllObjectDetect
+#from object_detect_full import FullObjectDetect
+#from object_detect_all import AllObjectDetect
 from object_detect_top_full import TopFullObjectDetect
 import object_detect_pb2
 import object_detect_pb2_grpc
@@ -69,7 +69,9 @@ def GetObjects(self, request, context):
       detectReply.location.right = object['box'][1]
       detectReply.location.top = object['box'][2]
       detectReply.location.bottom = object['box'][3]
-      detectReply.feature = object['feature']
+      #detectReply.feature = object['feature']
+      detectReply.color_code = object['color_code']
+      detectReply.color_score = object['color_score']
       yield  detectReply
 
 def serve():
diff --git a/grpc/object_detect_top.py b/grpc/object_detect_top.py
deleted file mode 100755
index 082d3da..0000000
--- a/grpc/object_detect_top.py
+++ /dev/null
@@ -1,213 +0,0 @@
-# coding: utf-8
-
-from __future__ import absolute_import
-
-import numpy as np
-import os
-from util import s3
-from PIL import Image
-import tensorflow as tf
-from object_detection.utils import visualization_utils as vis_util
-from stylelens_feature.feature_extract import ExtractFeature
-from bluelens_log import Logging
-
-import io
-from util import label_map_util
-
-TMP_CROP_IMG_FILE = './tmp.jpg'
-
-NUM_CLASSES = 1
-
-AWS_BUCKET = 'bluelens-style-model'
-AWS_BUCKET_FOLDER = 'object_detection'
-MODEL_TYPE = 'top'
-AWS_ACCESS_KEY = os.environ['AWS_ACCESS_KEY']
-AWS_SECRET_ACCESS_KEY = os.environ['AWS_SECRET_ACCESS_KEY']
-REDIS_SERVER = os.environ['REDIS_SERVER']
-REDIS_PASSWORD = os.environ['REDIS_PASSWORD']
-RELEASE_MODE = os.environ['RELEASE_MODE']
-FEATURE_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-FEATURE_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-OD_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_SCORE_MIN = float(os.environ['OD_SCORE_MIN'])
-GPU_NUM = os.environ['GPU_NUM']
-GPU = '/device:GPU:' + GPU_NUM
-
-MODEL_FILE = 'frozen_inference_graph.pb'
-LABEL_MAP_FILE = 'label_map.pbtxt'
-options = {
-  'REDIS_SERVER': REDIS_SERVER,
-  'REDIS_PASSWORD': REDIS_PASSWORD
-}
-log = Logging(options, tag='bl-detect:TopObjectDetect')
-storage = s3.S3(AWS_ACCESS_KEY, AWS_SECRET_ACCESS_KEY)
-
-class TopObjectDetect(object):
-  def __init__(self):
-    label_map_file = self.load_labelemap()
-    label_map = label_map_util.load_labelmap(label_map_file)
-    log.debug(label_map)
-    categories = label_map_util.convert_label_map_to_categories(label_map, max_num_classes=NUM_CLASSES,
-                                                                use_display_name=True)
-    self.__category_index = label_map_util.create_category_index(categories)
-    self.__detection_graph = tf.Graph()
-    self.__feature_extractor = ExtractFeature(use_gpu=True)
-    model_file = self.load_model()
-    with self.__detection_graph.as_default():
-      od_graph_def = tf.GraphDef()
-      with tf.gfile.GFile(model_file, 'rb') as fid:
-        serialized_graph = fid.read()
-        od_graph_def.ParseFromString(serialized_graph)
-        tf.import_graph_def(od_graph_def, name='')
-
-      with tf.device(GPU):
-        config = tf.ConfigProto()
-        config.gpu_options.allow_growth = True
-        self.__sess = tf.Session(config=config, graph=self.__detection_graph)
-
-    log.info('_init_ done')
-
-  def load_labelemap(self):
-    log.info('load_labelmap')
-    file = os.path.join(os.getcwd(), LABEL_MAP_FILE)
-    key = os.path.join(AWS_BUCKET_FOLDER, RELEASE_MODE, MODEL_TYPE, LABEL_MAP_FILE)
-    print(key)
-    try:
-      return storage.download_file_from_bucket(AWS_BUCKET, file, key)
-    except:
-      log.error('download error')
-      return None
-
-  def load_model(self):
-    log.info('load_model')
-    file = os.path.join(os.getcwd(), MODEL_FILE)
-    key = os.path.join(AWS_BUCKET_FOLDER, RELEASE_MODE, MODEL_TYPE, MODEL_FILE)
-    print(key)
-    try:
-      return storage.download_file_from_bucket(AWS_BUCKET, file, key)
-    except:
-      log.error('download error')
-      return None
-
-  def detect(self, image_bytes):
-
-    image_data = Image.open(io.BytesIO(image_bytes))
-    image_np = self.load_image_into_numpy_array(image_data)
-
-    show_box = False
-    out_image, boxes, scores, classes, num_detections = self.detect_objects(image_np, self.__sess, self.__detection_graph, show_box)
-
-    out_boxes = self.take_object(
-      out_image,
-      np.squeeze(boxes),
-      np.squeeze(scores),
-      np.squeeze(classes).astype(np.int32))
-
-    # log.debug(out_boxes)
-    return out_boxes
-
-  def take_object(self, image_np, boxes, scores, classes):
-    max_boxes_to_save = 3
-    taken_boxes = []
-    if not max_boxes_to_save:
-      max_boxes_to_save = boxes.shape[0]
-    for i in range(min(max_boxes_to_save, boxes.shape[0])):
-      if scores is None or scores[i] > OD_SCORE_MIN:
-        print(scores[i])
-        if classes[i] in self.__category_index.keys():
-          class_name = self.__category_index[classes[i]]['name']
-          class_code = str(self.__category_index[classes[i]]['id'])
-        else:
-          class_name = 'na'
-          class_code = 'na'
-        ymin, xmin, ymax, xmax = tuple(boxes[i].tolist())
-
-        use_normalized_coordinates = True
-        image_pil = Image.fromarray(np.uint8(image_np)).convert('RGB')
-
-        left, right, top, bottom = self.crop_bounding_box(
-          image_pil,
-          ymin,
-          xmin,
-          ymax,
-          xmax,
-          use_normalized_coordinates=use_normalized_coordinates)
-
-        feature_vector = self.extract_feature(image_pil, left, right, top, bottom)
-        item = {}
-
-        item['box'] = [left, right, top, bottom]
-        item['class_name'] = class_name
-        item['class_code'] = class_code
-        item['score'] = scores[i]
-        item['feature'] = feature_vector
-        taken_boxes.append(item)
-    return taken_boxes
-
-  def extract_feature(self, image, left, right, top, bottom):
-    area = (left, top, left + abs(left-right), top + abs(bottom-top))
-    cropped_img = image.crop(area)
-    cropped_img.save(TMP_CROP_IMG_FILE)
-    # cimage = io.BytesIO()
-    # cropped_img.save(cimage, format='JPEG')
-    # cimage.seek(0)  # rewind to the start
-    # cimage = Image.open(cimage)
-    feature = self.__feature_extractor.extract_feature(TMP_CROP_IMG_FILE)
-    return feature
-
-  def load_image_into_numpy_array(self, image):
-    (im_width, im_height) = image.size
-    return np.array(image.getdata()).reshape(
-      (im_height, im_width, 3)).astype(np.uint8)
-
-  def crop_bounding_box(self,
-                        image,
-                        ymin,
-                        xmin,
-                        ymax,
-                        xmax,
-                        use_normalized_coordinates=True):
-    im_width, im_height = image.size
-    # image.show()
-    if use_normalized_coordinates:
-      (left, right, top, bottom) = (xmin * im_width, xmax * im_width,
-                                    ymin * im_height, ymax * im_height)
-    else:
-      (left, right, top, bottom) = (xmin, xmax, ymin, ymax)
-
-    return left, right, top, bottom
-
-  def detect_objects(self, image_np, sess, detection_graph, show_box=True):
-    # Expand dimensions since the model expects images to have shape: [1, None, None, 3]
-    image_np_expanded = np.expand_dims(image_np, axis=0)
-    image_tensor = detection_graph.get_tensor_by_name('image_tensor:0')
-
-    # Each box represents a part of the image where a particular object was detected.
-    boxes = detection_graph.get_tensor_by_name('detection_boxes:0')
-
-    # Each score represent how level of confidence for each of the objects.
-    # Score is shown on the result image, together with the class label.
-    scores = detection_graph.get_tensor_by_name('detection_scores:0')
-    classes = detection_graph.get_tensor_by_name('detection_classes:0')
-    num_detections = detection_graph.get_tensor_by_name('num_detections:0')
-
-    # Actual detection.
-    (boxes, scores, classes, num_detections) = sess.run(
-      [boxes, scores, classes, num_detections],
-      feed_dict={image_tensor: image_np_expanded})
-
-    if show_box:
-      # Visualization of the results of a detection.
-      vis_util.visualize_boxes_and_labels_on_image_array(
-        image_np,
-        np.squeeze(boxes),
-        np.squeeze(classes).astype(np.int32),
-        np.squeeze(scores),
-        self.__category_index,
-        use_normalized_coordinates=True,
-        max_boxes_to_draw=3,
-        min_score_thresh=.05,
-        line_thickness=8)
-    # print(image_np)
-    return image_np, boxes, scores, classes, num_detections
diff --git a/grpc/object_detect_top_full.py b/grpc/object_detect_top_full.py
index 48d4f53..5a29b05 100644
--- a/grpc/object_detect_top_full.py
+++ b/grpc/object_detect_top_full.py
@@ -8,7 +8,8 @@
 from PIL import Image
 import tensorflow as tf
 from object_detection.utils import visualization_utils as vis_util
-from stylelens_feature.feature_extract import ExtractFeature
+#from stylelens_feature.feature_extract import ExtractFeature
+from stylelens_color.color_extract import ExtractColor
 from bluelens_log import Logging
 
 import io
@@ -26,10 +27,14 @@
 REDIS_SERVER = os.environ['REDIS_SERVER']
 REDIS_PASSWORD = os.environ['REDIS_PASSWORD']
 RELEASE_MODE = os.environ['RELEASE_MODE']
-FEATURE_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-FEATURE_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
-OD_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
-OD_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
+COLOR_GRPC_HOST = os.environ['COLOR_GRPC_HOST']
+COLOR_GRPC_PORT = os.environ['COLOR_GRPC_HOST']
+OD_GRPC_HOST = os.environ['COLOR_GRPC_HOST']
+OD_GRPC_PORT = os.environ['COLOR_GRPC_PORT']
+#FEATURE_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
+#FEATURE_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
+#OD_GRPC_HOST = os.environ['FEATURE_GRPC_HOST']
+#OD_GRPC_PORT = os.environ['FEATURE_GRPC_PORT']
 OD_SCORE_MIN = float(os.environ['OD_SCORE_MIN'])
 GPU_NUM = os.environ['GPU_NUM']
 GPU = '/device:GPU:' + GPU_NUM
@@ -52,7 +57,8 @@ def __init__(self):
                                                                 use_display_name=True)
     self.__category_index = label_map_util.create_category_index(categories)
     self.__detection_graph = tf.Graph()
-    self.__feature_extractor = ExtractFeature(use_gpu=True)
+    #self.__feature_extractor = ExtractFeature(use_gpu=True)
+    self.__color_extractor = ExtractColor(use_gpu=True)
     model_file = self.load_model()
     with self.__detection_graph.as_default():
       od_graph_def = tf.GraphDef()
@@ -134,7 +140,9 @@ def take_object(self, image_np, boxes, scores, classes):
           xmax,
           use_normalized_coordinates=use_normalized_coordinates)
 
-        feature_vector = self.extract_feature(image_pil, left, right, top, bottom)
+        #feature_vector = self.extract_feature(image_pil, left, right, top, bottom)
+        color = self.extract_color(image_pil, left, right, top, bottom)
+
         item = {}
 
         item['box'] = [left, right, top, bottom]
@@ -147,10 +155,12 @@ def take_object(self, image_np, boxes, scores, classes):
         else:
           item['class_code'] = class_code
         item['score'] = scores[i]
-        item['feature'] = feature_vector
+        #item['feature'] = feature_vector
+        item['color_code'] = color['class_code']
+        item['color_score'] = color['class_score']
         taken_boxes.append(item)
     return taken_boxes
-
+  """
   def extract_feature(self, image, left, right, top, bottom):
     area = (left, top, left + abs(left-right), top + abs(bottom-top))
     cropped_img = image.crop(area)
@@ -161,6 +171,13 @@ def extract_feature(self, image, left, right, top, bottom):
     # cimage = Image.open(cimage)
     feature = self.__feature_extractor.extract_feature(TMP_CROP_IMG_FILE)
     return feature
+  """
+  def extract_color(self, image, left, right, top, bottom):
+    area = (left, top, left + abs(left-right), top + abs(bottom-top))
+    cropped_img = image.crop(area)
+    cropped_img.save(TMP_CROP_IMG_FILE)
+    color = self.__color_extractor.extract_color(TMP_CROP_IMG_FILE)
+    return color
 
   def load_image_into_numpy_array(self, image):
     (im_width, im_height) = image.size
diff --git a/protos/object_detect.proto b/protos/object_detect.proto
index a5078ef..6449299 100644
--- a/protos/object_detect.proto
+++ b/protos/object_detect.proto
@@ -41,5 +41,7 @@ message DetectReply {
     string class_name = 2;
     string class_code = 3;
     float  score = 4;
-    bytes feature = 5;
+    string color_code = 5;
+    float color_score = 6;
+    //bytes feature = 5;
 }
diff --git a/requirements.txt b/requirements.txt
index 8bc8d9c..9bbaf52 100644
--- a/requirements.txt
+++ b/requirements.txt
@@ -20,5 +20,6 @@ s3transfer==0.1.12
 six==1.11.0
 tensorflow-gpu==1.4.1
 stylelens-feature==1.0.8
+stylelens-color==1.0.3
 urllib3==1.22
 Werkzeug==0.14.1
diff --git a/stylelens/bin/activate b/stylelens/bin/activate
new file mode 100644
index 0000000..a4e1791
--- /dev/null
+++ b/stylelens/bin/activate
@@ -0,0 +1,78 @@
+# This file must be used with "source bin/activate" *from bash*
+# you cannot run it directly
+
+deactivate () {
+    unset -f pydoc >/dev/null 2>&1
+
+    # reset old environment variables
+    # ! [ -z ${VAR+_} ] returns true if VAR is declared at all
+    if ! [ -z "${_OLD_VIRTUAL_PATH+_}" ] ; then
+        PATH="$_OLD_VIRTUAL_PATH"
+        export PATH
+        unset _OLD_VIRTUAL_PATH
+    fi
+    if ! [ -z "${_OLD_VIRTUAL_PYTHONHOME+_}" ] ; then
+        PYTHONHOME="$_OLD_VIRTUAL_PYTHONHOME"
+        export PYTHONHOME
+        unset _OLD_VIRTUAL_PYTHONHOME
+    fi
+
+    # This should detect bash and zsh, which have a hash command that must
+    # be called to get it to forget past commands.  Without forgetting
+    # past commands the $PATH changes we made may not be respected
+    if [ -n "${BASH-}" ] || [ -n "${ZSH_VERSION-}" ] ; then
+        hash -r 2>/dev/null
+    fi
+
+    if ! [ -z "${_OLD_VIRTUAL_PS1+_}" ] ; then
+        PS1="$_OLD_VIRTUAL_PS1"
+        export PS1
+        unset _OLD_VIRTUAL_PS1
+    fi
+
+    unset VIRTUAL_ENV
+    if [ ! "${1-}" = "nondestructive" ] ; then
+    # Self destruct!
+        unset -f deactivate
+    fi
+}
+
+# unset irrelevant variables
+deactivate nondestructive
+
+VIRTUAL_ENV="/Users/lion/PycharmProjects/bl-detect/stylelens"
+export VIRTUAL_ENV
+
+_OLD_VIRTUAL_PATH="$PATH"
+PATH="$VIRTUAL_ENV/bin:$PATH"
+export PATH
+
+# unset PYTHONHOME if set
+if ! [ -z "${PYTHONHOME+_}" ] ; then
+    _OLD_VIRTUAL_PYTHONHOME="$PYTHONHOME"
+    unset PYTHONHOME
+fi
+
+if [ -z "${VIRTUAL_ENV_DISABLE_PROMPT-}" ] ; then
+    _OLD_VIRTUAL_PS1="$PS1"
+    if [ "x" != x ] ; then
+        PS1="$PS1"
+    else
+        PS1="(`basename \"$VIRTUAL_ENV\"`) $PS1"
+    fi
+    export PS1
+fi
+
+# Make sure to unalias pydoc if it's already there
+alias pydoc 2>/dev/null >/dev/null && unalias pydoc
+
+pydoc () {
+    python -m pydoc "$@"
+}
+
+# This should detect bash and zsh, which have a hash command that must
+# be called to get it to forget past commands.  Without forgetting
+# past commands the $PATH changes we made may not be respected
+if [ -n "${BASH-}" ] || [ -n "${ZSH_VERSION-}" ] ; then
+    hash -r 2>/dev/null
+fi
diff --git a/stylelens/bin/activate.csh b/stylelens/bin/activate.csh
new file mode 100644
index 0000000..cd764e7
--- /dev/null
+++ b/stylelens/bin/activate.csh
@@ -0,0 +1,36 @@
+# This file must be used with "source bin/activate.csh" *from csh*.
+# You cannot run it directly.
+# Created by Davide Di Blasi <davidedb@gmail.com>.
+
+alias deactivate 'test $?_OLD_VIRTUAL_PATH != 0 && setenv PATH "$_OLD_VIRTUAL_PATH" && unset _OLD_VIRTUAL_PATH; rehash; test $?_OLD_VIRTUAL_PROMPT != 0 && set prompt="$_OLD_VIRTUAL_PROMPT" && unset _OLD_VIRTUAL_PROMPT; unsetenv VIRTUAL_ENV; test "\!:*" != "nondestructive" && unalias deactivate && unalias pydoc'
+
+# Unset irrelevant variables.
+deactivate nondestructive
+
+setenv VIRTUAL_ENV "/Users/lion/PycharmProjects/bl-detect/stylelens"
+
+set _OLD_VIRTUAL_PATH="$PATH"
+setenv PATH "$VIRTUAL_ENV/bin:$PATH"
+
+
+
+if ("" != "") then
+    set env_name = ""
+else
+    set env_name = `basename "$VIRTUAL_ENV"`
+endif
+
+# Could be in a non-interactive environment,
+# in which case, $prompt is undefined and we wouldn't
+# care about the prompt anyway.
+if ( $?prompt ) then
+    set _OLD_VIRTUAL_PROMPT="$prompt"
+    set prompt = "[$env_name] $prompt"
+endif
+
+unset env_name
+
+alias pydoc python -m pydoc
+
+rehash
+
diff --git a/stylelens/bin/activate.fish b/stylelens/bin/activate.fish
new file mode 100644
index 0000000..70e1a07
--- /dev/null
+++ b/stylelens/bin/activate.fish
@@ -0,0 +1,76 @@
+# This file must be used using `. bin/activate.fish` *within a running fish ( http://fishshell.com ) session*.
+# Do not run it directly.
+
+function deactivate -d 'Exit virtualenv mode and return to the normal environment.'
+    # reset old environment variables
+    if test -n "$_OLD_VIRTUAL_PATH"
+        set -gx PATH $_OLD_VIRTUAL_PATH
+        set -e _OLD_VIRTUAL_PATH
+    end
+
+    if test -n "$_OLD_VIRTUAL_PYTHONHOME"
+        set -gx PYTHONHOME $_OLD_VIRTUAL_PYTHONHOME
+        set -e _OLD_VIRTUAL_PYTHONHOME
+    end
+
+    if test -n "$_OLD_FISH_PROMPT_OVERRIDE"
+        # Set an empty local `$fish_function_path` to allow the removal of `fish_prompt` using `functions -e`.
+        set -l fish_function_path
+
+        # Erase virtualenv's `fish_prompt` and restore the original.
+        functions -e fish_prompt
+        functions -c _old_fish_prompt fish_prompt
+        functions -e _old_fish_prompt
+        set -e _OLD_FISH_PROMPT_OVERRIDE
+    end
+
+    set -e VIRTUAL_ENV
+
+    if test "$argv[1]" != 'nondestructive'
+        # Self-destruct!
+        functions -e pydoc
+        functions -e deactivate
+    end
+end
+
+# Unset irrelevant variables.
+deactivate nondestructive
+
+set -gx VIRTUAL_ENV "/Users/lion/PycharmProjects/bl-detect/stylelens"
+
+set -gx _OLD_VIRTUAL_PATH $PATH
+set -gx PATH "$VIRTUAL_ENV/bin" $PATH
+
+# Unset `$PYTHONHOME` if set.
+if set -q PYTHONHOME
+    set -gx _OLD_VIRTUAL_PYTHONHOME $PYTHONHOME
+    set -e PYTHONHOME
+end
+
+function pydoc
+    python -m pydoc $argv
+end
+
+if test -z "$VIRTUAL_ENV_DISABLE_PROMPT"
+    # Copy the current `fish_prompt` function as `_old_fish_prompt`.
+    functions -c fish_prompt _old_fish_prompt
+
+    function fish_prompt
+        # Save the current $status, for fish_prompts that display it.
+        set -l old_status $status
+
+        # Prompt override provided?
+        # If not, just prepend the environment name.
+        if test -n ""
+            printf '%s%s' "" (set_color normal)
+        else
+            printf '%s(%s) ' (set_color normal) (basename "$VIRTUAL_ENV")
+        end
+
+        # Restore the original $status
+        echo "exit $old_status" | source
+        _old_fish_prompt
+    end
+
+    set -gx _OLD_FISH_PROMPT_OVERRIDE "$VIRTUAL_ENV"
+end
diff --git a/stylelens/bin/activate_this.py b/stylelens/bin/activate_this.py
new file mode 100644
index 0000000..f18193b
--- /dev/null
+++ b/stylelens/bin/activate_this.py
@@ -0,0 +1,34 @@
+"""By using execfile(this_file, dict(__file__=this_file)) you will
+activate this virtualenv environment.
+
+This can be used when you must use an existing Python interpreter, not
+the virtualenv bin/python
+"""
+
+try:
+    __file__
+except NameError:
+    raise AssertionError(
+        "You must run this like execfile('path/to/activate_this.py', dict(__file__='path/to/activate_this.py'))")
+import sys
+import os
+
+old_os_path = os.environ.get('PATH', '')
+os.environ['PATH'] = os.path.dirname(os.path.abspath(__file__)) + os.pathsep + old_os_path
+base = os.path.dirname(os.path.dirname(os.path.abspath(__file__)))
+if sys.platform == 'win32':
+    site_packages = os.path.join(base, 'Lib', 'site-packages')
+else:
+    site_packages = os.path.join(base, 'lib', 'python%s' % sys.version[:3], 'site-packages')
+prev_sys_path = list(sys.path)
+import site
+site.addsitedir(site_packages)
+sys.real_prefix = sys.prefix
+sys.prefix = base
+# Move the added items to the front of the path:
+new_sys_path = []
+for item in list(sys.path):
+    if item not in prev_sys_path:
+        new_sys_path.append(item)
+        sys.path.remove(item)
+sys.path[:0] = new_sys_path
diff --git a/stylelens/bin/easy_install b/stylelens/bin/easy_install
new file mode 100755
index 0000000..cc9d7d2
--- /dev/null
+++ b/stylelens/bin/easy_install
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python3.6
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from setuptools.command.easy_install import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/easy_install-3.6 b/stylelens/bin/easy_install-3.6
new file mode 100755
index 0000000..cc9d7d2
--- /dev/null
+++ b/stylelens/bin/easy_install-3.6
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python3.6
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from setuptools.command.easy_install import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/enhancer.py b/stylelens/bin/enhancer.py
new file mode 100755
index 0000000..be7c08d
--- /dev/null
+++ b/stylelens/bin/enhancer.py
@@ -0,0 +1,64 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+# this demo script creates four windows containing an image and a slider.
+# drag the slider to modify the image.
+#
+
+import sys
+
+if sys.version_info[0] > 2:
+    import tkinter
+else:
+    import Tkinter as tkinter
+
+from PIL import Image, ImageTk, ImageEnhance
+
+#
+# enhancer widget
+
+
+class Enhance(tkinter.Frame):
+    def __init__(self, master, image, name, enhancer, lo, hi):
+        tkinter.Frame.__init__(self, master)
+
+        # set up the image
+        self.tkim = ImageTk.PhotoImage(image.mode, image.size)
+        self.enhancer = enhancer(image)
+        self.update("1.0")  # normalize
+
+        # image window
+        tkinter.Label(self, image=self.tkim).pack()
+
+        # scale
+        s = tkinter.Scale(self, label=name, orient=tkinter.HORIZONTAL,
+                  from_=lo, to=hi, resolution=0.01,
+                  command=self.update)
+        s.set(self.value)
+        s.pack()
+
+    def update(self, value):
+        self.value = float(value)
+        self.tkim.paste(self.enhancer.enhance(self.value))
+
+#
+# main
+
+if len(sys.argv) != 2:
+    print("Usage: enhancer file")
+    sys.exit(1)
+
+root = tkinter.Tk()
+
+im = Image.open(sys.argv[1])
+
+im.thumbnail((200, 200))
+
+Enhance(root, im, "Color", ImageEnhance.Color, 0.0, 4.0).pack()
+Enhance(tkinter.Toplevel(), im, "Sharpness", ImageEnhance.Sharpness, -2.0, 2.0).pack()
+Enhance(tkinter.Toplevel(), im, "Brightness", ImageEnhance.Brightness, -1.0, 3.0).pack()
+Enhance(tkinter.Toplevel(), im, "Contrast", ImageEnhance.Contrast, -1.0, 3.0).pack()
+
+root.mainloop()
diff --git a/stylelens/bin/explode.py b/stylelens/bin/explode.py
new file mode 100755
index 0000000..1c02baf
--- /dev/null
+++ b/stylelens/bin/explode.py
@@ -0,0 +1,112 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+# split an animation into a number of frame files
+#
+
+from __future__ import print_function
+
+from PIL import Image
+import os
+import sys
+
+
+class Interval(object):
+
+    def __init__(self, interval="0"):
+
+        self.setinterval(interval)
+
+    def setinterval(self, interval):
+
+        self.hilo = []
+
+        for s in interval.split(","):
+            if not s.strip():
+                continue
+            try:
+                v = int(s)
+                if v < 0:
+                    lo, hi = 0, -v
+                else:
+                    lo = hi = v
+            except ValueError:
+                i = s.find("-")
+                lo, hi = int(s[:i]), int(s[i+1:])
+
+            self.hilo.append((hi, lo))
+
+        if not self.hilo:
+            self.hilo = [(sys.maxsize, 0)]
+
+    def __getitem__(self, index):
+
+        for hi, lo in self.hilo:
+            if hi >= index >= lo:
+                return 1
+        return 0
+
+# --------------------------------------------------------------------
+# main program
+
+html = 0
+
+if sys.argv[1:2] == ["-h"]:
+    html = 1
+    del sys.argv[1]
+
+if not sys.argv[2:]:
+    print()
+    print("Syntax: python explode.py infile template [range]")
+    print()
+    print("The template argument is used to construct the names of the")
+    print("individual frame files.  The frames are numbered file001.ext,")
+    print("file002.ext, etc.  You can insert %d to control the placement")
+    print("and syntax of the frame number.")
+    print()
+    print("The optional range argument specifies which frames to extract.")
+    print("You can give one or more ranges like 1-10, 5, -15 etc.  If")
+    print("omitted, all frames are extracted.")
+    sys.exit(1)
+
+infile = sys.argv[1]
+outfile = sys.argv[2]
+
+frames = Interval(",".join(sys.argv[3:]))
+
+try:
+    # check if outfile contains a placeholder
+    outfile % 1
+except TypeError:
+    file, ext = os.path.splitext(outfile)
+    outfile = file + "%03d" + ext
+
+ix = 1
+
+im = Image.open(infile)
+
+if html:
+    file, ext = os.path.splitext(outfile)
+    html = open(file+".html", "w")
+    html.write("<html>\n<body>\n")
+
+while True:
+
+    if frames[ix]:
+        im.save(outfile % ix)
+        print(outfile % ix)
+
+        if html:
+            html.write("<img src='%s'><br>\n" % outfile % ix)
+
+    try:
+        im.seek(ix)
+    except EOFError:
+        break
+
+    ix += 1
+
+if html:
+    html.write("</body>\n</html>\n")
diff --git a/stylelens/bin/f2py b/stylelens/bin/f2py
new file mode 100755
index 0000000..03aafd4
--- /dev/null
+++ b/stylelens/bin/f2py
@@ -0,0 +1,28 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+# See http://cens.ioc.ee/projects/f2py2e/
+from __future__ import division, print_function
+
+import os
+import sys
+for mode in ["g3-numpy", "2e-numeric", "2e-numarray", "2e-numpy"]:
+    try:
+        i = sys.argv.index("--" + mode)
+        del sys.argv[i]
+        break
+    except ValueError:
+        pass
+os.environ["NO_SCIPY_IMPORT"] = "f2py"
+if mode == "g3-numpy":
+    sys.stderr.write("G3 f2py support is not implemented, yet.\\n")
+    sys.exit(1)
+elif mode == "2e-numeric":
+    from f2py2e import main
+elif mode == "2e-numarray":
+    sys.argv.append("-DNUMARRAY")
+    from f2py2e import main
+elif mode == "2e-numpy":
+    from numpy.f2py import main
+else:
+    sys.stderr.write("Unknown mode: " + repr(mode) + "\\n")
+    sys.exit(1)
+main()
diff --git a/stylelens/bin/freeze_graph b/stylelens/bin/freeze_graph
new file mode 100755
index 0000000..1faad2b
--- /dev/null
+++ b/stylelens/bin/freeze_graph
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from tensorflow.python.tools.freeze_graph import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/gifmaker.py b/stylelens/bin/gifmaker.py
new file mode 100755
index 0000000..093d7be
--- /dev/null
+++ b/stylelens/bin/gifmaker.py
@@ -0,0 +1,31 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+# convert sequence format to GIF animation
+#
+# history:
+#       97-01-03 fl     created
+#
+# Copyright (c) Secret Labs AB 1997.  All rights reserved.
+# Copyright (c) Fredrik Lundh 1997.
+#
+# See the README file for information on usage and redistribution.
+#
+
+from __future__ import print_function
+
+from PIL import Image
+
+if __name__ == "__main__":
+
+    import sys
+
+    if len(sys.argv) < 3:
+        print("GIFMAKER -- create GIF animations")
+        print("Usage: gifmaker infile outfile")
+        sys.exit(1)
+
+    im = Image.open(sys.argv[1])
+    im.save(sys.argv[2], save_all=True)
diff --git a/stylelens/bin/jp.py b/stylelens/bin/jp.py
new file mode 100755
index 0000000..64e3512
--- /dev/null
+++ b/stylelens/bin/jp.py
@@ -0,0 +1,54 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+import sys
+import json
+import argparse
+from pprint import pformat
+
+import jmespath
+from jmespath import exceptions
+
+
+def main():
+    parser = argparse.ArgumentParser()
+    parser.add_argument('expression')
+    parser.add_argument('-f', '--filename',
+                        help=('The filename containing the input data.  '
+                              'If a filename is not given then data is '
+                              'read from stdin.'))
+    parser.add_argument('--ast', action='store_true',
+                        help=('Pretty print the AST, do not search the data.'))
+    args = parser.parse_args()
+    expression = args.expression
+    if args.ast:
+        # Only print the AST
+        expression = jmespath.compile(args.expression)
+        sys.stdout.write(pformat(expression.parsed))
+        sys.stdout.write('\n')
+        return 0
+    if args.filename:
+        with open(args.filename, 'r') as f:
+            data = json.load(f)
+    else:
+        data = sys.stdin.read()
+        data = json.loads(data)
+    try:
+        sys.stdout.write(json.dumps(
+            jmespath.search(expression, data), indent=4))
+        sys.stdout.write('\n')
+    except exceptions.ArityError as e:
+        sys.stderr.write("invalid-arity: %s\n" % e)
+        return 1
+    except exceptions.JMESPathTypeError as e:
+        sys.stderr.write("invalid-type: %s\n" % e)
+        return 1
+    except exceptions.UnknownFunctionError as e:
+        sys.stderr.write("unknown-function: %s\n" % e)
+        return 1
+    except exceptions.ParseError as e:
+        sys.stderr.write("syntax-error: %s\n" % e)
+        return 1
+
+
+if __name__ == '__main__':
+    sys.exit(main())
diff --git a/stylelens/bin/markdown_py b/stylelens/bin/markdown_py
new file mode 100755
index 0000000..7b15f7c
--- /dev/null
+++ b/stylelens/bin/markdown_py
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from markdown.__main__ import run
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(run())
diff --git a/stylelens/bin/painter.py b/stylelens/bin/painter.py
new file mode 100755
index 0000000..082353b
--- /dev/null
+++ b/stylelens/bin/painter.py
@@ -0,0 +1,84 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+# this demo script illustrates pasting into an already displayed
+# photoimage.  note that the current version of Tk updates the whole
+# image every time we paste, so to get decent performance, we split
+# the image into a set of tiles.
+#
+
+import sys
+
+if sys.version_info[0] > 2:
+    import tkinter
+else:
+    import Tkinter as tkinter
+
+from PIL import Image, ImageTk
+
+#
+# painter widget
+
+
+class PaintCanvas(tkinter.Canvas):
+    def __init__(self, master, image):
+        tkinter.Canvas.__init__(self, master,
+                                width=image.size[0], height=image.size[1])
+
+        # fill the canvas
+        self.tile = {}
+        self.tilesize = tilesize = 32
+        xsize, ysize = image.size
+        for x in range(0, xsize, tilesize):
+            for y in range(0, ysize, tilesize):
+                box = x, y, min(xsize, x+tilesize), min(ysize, y+tilesize)
+                tile = ImageTk.PhotoImage(image.crop(box))
+                self.create_image(x, y, image=tile, anchor=tkinter.NW)
+                self.tile[(x, y)] = box, tile
+
+        self.image = image
+
+        self.bind("<B1-Motion>", self.paint)
+
+    def paint(self, event):
+        xy = event.x - 10, event.y - 10, event.x + 10, event.y + 10
+        im = self.image.crop(xy)
+
+        # process the image in some fashion
+        im = im.convert("L")
+
+        self.image.paste(im, xy)
+        self.repair(xy)
+
+    def repair(self, box):
+        # update canvas
+        dx = box[0] % self.tilesize
+        dy = box[1] % self.tilesize
+        for x in range(box[0]-dx, box[2]+1, self.tilesize):
+            for y in range(box[1]-dy, box[3]+1, self.tilesize):
+                try:
+                    xy, tile = self.tile[(x, y)]
+                    tile.paste(self.image.crop(xy))
+                except KeyError:
+                    pass  # outside the image
+        self.update_idletasks()
+
+#
+# main
+
+if len(sys.argv) != 2:
+    print("Usage: painter file")
+    sys.exit(1)
+
+root = tkinter.Tk()
+
+im = Image.open(sys.argv[1])
+
+if im.mode != "RGB":
+    im = im.convert("RGB")
+
+PaintCanvas(root, im).pack()
+
+root.mainloop()
diff --git a/stylelens/bin/pilconvert.py b/stylelens/bin/pilconvert.py
new file mode 100755
index 0000000..2256b17
--- /dev/null
+++ b/stylelens/bin/pilconvert.py
@@ -0,0 +1,99 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library.
+# $Id$
+#
+# convert image files
+#
+# History:
+# 0.1   96-04-20 fl     Created
+# 0.2   96-10-04 fl     Use draft mode when converting images
+# 0.3   96-12-30 fl     Optimize output (PNG, JPEG)
+# 0.4   97-01-18 fl     Made optimize an option (PNG, JPEG)
+# 0.5   98-12-30 fl     Fixed -f option (from Anthony Baxter)
+#
+
+from __future__ import print_function
+
+import getopt
+import string
+import sys
+
+from PIL import Image
+
+
+def usage():
+    print("PIL Convert 0.5/1998-12-30 -- convert image files")
+    print("Usage: pilconvert [option] infile outfile")
+    print()
+    print("Options:")
+    print()
+    print("  -c <format>  convert to format (default is given by extension)")
+    print()
+    print("  -g           convert to greyscale")
+    print("  -p           convert to palette image (using standard palette)")
+    print("  -r           convert to rgb")
+    print()
+    print("  -o           optimize output (trade speed for size)")
+    print("  -q <value>   set compression quality (0-100, JPEG only)")
+    print()
+    print("  -f           list supported file formats")
+    sys.exit(1)
+
+if len(sys.argv) == 1:
+    usage()
+
+try:
+    opt, argv = getopt.getopt(sys.argv[1:], "c:dfgopq:r")
+except getopt.error as v:
+    print(v)
+    sys.exit(1)
+
+output_format = None
+convert = None
+
+options = {}
+
+for o, a in opt:
+
+    if o == "-f":
+        Image.init()
+        id = sorted(Image.ID)
+        print("Supported formats (* indicates output format):")
+        for i in id:
+            if i in Image.SAVE:
+                print(i+"*", end=' ')
+            else:
+                print(i, end=' ')
+        sys.exit(1)
+
+    elif o == "-c":
+        output_format = a
+
+    if o == "-g":
+        convert = "L"
+    elif o == "-p":
+        convert = "P"
+    elif o == "-r":
+        convert = "RGB"
+
+    elif o == "-o":
+        options["optimize"] = 1
+    elif o == "-q":
+        options["quality"] = string.atoi(a)
+
+if len(argv) != 2:
+    usage()
+
+try:
+    im = Image.open(argv[0])
+    if convert and im.mode != convert:
+        im.draft(convert, im.size)
+        im = im.convert(convert)
+    if output_format:
+        im.save(argv[1], output_format, **options)
+    else:
+        im.save(argv[1], **options)
+except:
+    print("cannot convert image", end=' ')
+    print("(%s:%s)" % (sys.exc_info()[0], sys.exc_info()[1]))
diff --git a/stylelens/bin/pildriver.py b/stylelens/bin/pildriver.py
new file mode 100755
index 0000000..e75c36c
--- /dev/null
+++ b/stylelens/bin/pildriver.py
@@ -0,0 +1,526 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+"""PILdriver, an image-processing calculator using PIL.
+
+An instance of class PILDriver is essentially a software stack machine
+(Polish-notation interpreter) for sequencing PIL image
+transformations.  The state of the instance is the interpreter stack.
+
+The only method one will normally invoke after initialization is the
+`execute' method.  This takes an argument list of tokens, pushes them
+onto the instance's stack, and then tries to clear the stack by
+successive evaluation of PILdriver operators.  Any part of the stack
+not cleaned off persists and is part of the evaluation context for
+the next call of the execute method.
+
+PILDriver doesn't catch any exceptions, on the theory that these
+are actually diagnostic information that should be interpreted by
+the calling code.
+
+When called as a script, the command-line arguments are passed to
+a PILDriver instance.  If there are no command-line arguments, the
+module runs an interactive interpreter, each line of which is split into
+space-separated tokens and passed to the execute method.
+
+In the method descriptions below, a first line beginning with the string
+`usage:' means this method can be invoked with the token that follows
+it.  Following <>-enclosed arguments describe how the method interprets
+the entries on the stack.  Each argument specification begins with a
+type specification: either `int', `float', `string', or `image'.
+
+All operations consume their arguments off the stack (use `dup' to
+keep copies around).  Use `verbose 1' to see the stack state displayed
+before each operation.
+
+Usage examples:
+
+    `show crop 0 0 200 300 open test.png' loads test.png, crops out a portion
+of its upper-left-hand corner and displays the cropped portion.
+
+    `save rotated.png rotate 30 open test.tiff' loads test.tiff, rotates it
+30 degrees, and saves the result as rotated.png (in PNG format).
+"""
+# by Eric S. Raymond <esr@thyrsus.com>
+# $Id$
+
+# TO DO:
+# 1. Add PILFont capabilities, once that's documented.
+# 2. Add PILDraw operations.
+# 3. Add support for composing and decomposing multiple-image files.
+#
+
+from __future__ import print_function
+
+from PIL import Image
+
+
+class PILDriver(object):
+
+    verbose = 0
+
+    def do_verbose(self):
+        """usage: verbose <int:num>
+
+        Set verbosity flag from top of stack.
+        """
+        self.verbose = int(self.do_pop())
+
+    # The evaluation stack (internal only)
+
+    stack = []          # Stack of pending operations
+
+    def push(self, item):
+        "Push an argument onto the evaluation stack."
+        self.stack.insert(0, item)
+
+    def top(self):
+        "Return the top-of-stack element."
+        return self.stack[0]
+
+    # Stack manipulation (callable)
+
+    def do_clear(self):
+        """usage: clear
+
+        Clear the stack.
+        """
+        self.stack = []
+
+    def do_pop(self):
+        """usage: pop
+
+        Discard the top element on the stack.
+        """
+        return self.stack.pop(0)
+
+    def do_dup(self):
+        """usage: dup
+
+        Duplicate the top-of-stack item.
+        """
+        if hasattr(self, 'format'):     # If it's an image, do a real copy
+            dup = self.stack[0].copy()
+        else:
+            dup = self.stack[0]
+        self.push(dup)
+
+    def do_swap(self):
+        """usage: swap
+
+        Swap the top-of-stack item with the next one down.
+        """
+        self.stack = [self.stack[1], self.stack[0]] + self.stack[2:]
+
+    # Image module functions (callable)
+
+    def do_new(self):
+        """usage: new <int:xsize> <int:ysize> <int:color>:
+
+        Create and push a greyscale image of given size and color.
+        """
+        xsize = int(self.do_pop())
+        ysize = int(self.do_pop())
+        color = int(self.do_pop())
+        self.push(Image.new("L", (xsize, ysize), color))
+
+    def do_open(self):
+        """usage: open <string:filename>
+
+        Open the indicated image, read it, push the image on the stack.
+        """
+        self.push(Image.open(self.do_pop()))
+
+    def do_blend(self):
+        """usage: blend <image:pic1> <image:pic2> <float:alpha>
+
+        Replace two images and an alpha with the blended image.
+        """
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        alpha = float(self.do_pop())
+        self.push(Image.blend(image1, image2, alpha))
+
+    def do_composite(self):
+        """usage: composite <image:pic1> <image:pic2> <image:mask>
+
+        Replace two images and a mask with their composite.
+        """
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        mask = self.do_pop()
+        self.push(Image.composite(image1, image2, mask))
+
+    def do_merge(self):
+        """usage: merge <string:mode> <image:pic1>
+                        [<image:pic2> [<image:pic3> [<image:pic4>]]]
+
+        Merge top-of stack images in a way described by the mode.
+        """
+        mode = self.do_pop()
+        bandlist = []
+        for band in mode:
+            bandlist.append(self.do_pop())
+        self.push(Image.merge(mode, bandlist))
+
+    # Image class methods
+
+    def do_convert(self):
+        """usage: convert <string:mode> <image:pic1>
+
+        Convert the top image to the given mode.
+        """
+        mode = self.do_pop()
+        image = self.do_pop()
+        self.push(image.convert(mode))
+
+    def do_copy(self):
+        """usage: copy <image:pic1>
+
+        Make and push a true copy of the top image.
+        """
+        self.dup()
+
+    def do_crop(self):
+        """usage: crop <int:left> <int:upper> <int:right> <int:lower>
+                       <image:pic1>
+
+        Crop and push a rectangular region from the current image.
+        """
+        left = int(self.do_pop())
+        upper = int(self.do_pop())
+        right = int(self.do_pop())
+        lower = int(self.do_pop())
+        image = self.do_pop()
+        self.push(image.crop((left, upper, right, lower)))
+
+    def do_draft(self):
+        """usage: draft <string:mode> <int:xsize> <int:ysize>
+
+        Configure the loader for a given mode and size.
+        """
+        mode = self.do_pop()
+        xsize = int(self.do_pop())
+        ysize = int(self.do_pop())
+        self.push(self.draft(mode, (xsize, ysize)))
+
+    def do_filter(self):
+        """usage: filter <string:filtername> <image:pic1>
+
+        Process the top image with the given filter.
+        """
+        from PIL import ImageFilter
+        imageFilter = getattr(ImageFilter, self.do_pop().upper())
+        image = self.do_pop()
+        self.push(image.filter(imageFilter))
+
+    def do_getbbox(self):
+        """usage: getbbox
+
+        Push left, upper, right, and lower pixel coordinates of the top image.
+        """
+        bounding_box = self.do_pop().getbbox()
+        self.push(bounding_box[3])
+        self.push(bounding_box[2])
+        self.push(bounding_box[1])
+        self.push(bounding_box[0])
+
+    def do_getextrema(self):
+        """usage: extrema
+
+        Push minimum and maximum pixel values of the top image.
+        """
+        extrema = self.do_pop().extrema()
+        self.push(extrema[1])
+        self.push(extrema[0])
+
+    def do_offset(self):
+        """usage: offset <int:xoffset> <int:yoffset> <image:pic1>
+
+        Offset the pixels in the top image.
+        """
+        xoff = int(self.do_pop())
+        yoff = int(self.do_pop())
+        image = self.do_pop()
+        self.push(image.offset(xoff, yoff))
+
+    def do_paste(self):
+        """usage: paste <image:figure> <int:xoffset> <int:yoffset>
+                        <image:ground>
+
+        Paste figure image into ground with upper left at given offsets.
+        """
+        figure = self.do_pop()
+        xoff = int(self.do_pop())
+        yoff = int(self.do_pop())
+        ground = self.do_pop()
+        if figure.mode == "RGBA":
+            ground.paste(figure, (xoff, yoff), figure)
+        else:
+            ground.paste(figure, (xoff, yoff))
+        self.push(ground)
+
+    def do_resize(self):
+        """usage: resize <int:xsize> <int:ysize> <image:pic1>
+
+        Resize the top image.
+        """
+        ysize = int(self.do_pop())
+        xsize = int(self.do_pop())
+        image = self.do_pop()
+        self.push(image.resize((xsize, ysize)))
+
+    def do_rotate(self):
+        """usage: rotate <int:angle> <image:pic1>
+
+        Rotate image through a given angle
+        """
+        angle = int(self.do_pop())
+        image = self.do_pop()
+        self.push(image.rotate(angle))
+
+    def do_save(self):
+        """usage: save <string:filename> <image:pic1>
+
+        Save image with default options.
+        """
+        filename = self.do_pop()
+        image = self.do_pop()
+        image.save(filename)
+
+    def do_save2(self):
+        """usage: save2 <string:filename> <string:options> <image:pic1>
+
+        Save image with specified options.
+        """
+        filename = self.do_pop()
+        options = self.do_pop()
+        image = self.do_pop()
+        image.save(filename, None, options)
+
+    def do_show(self):
+        """usage: show <image:pic1>
+
+        Display and pop the top image.
+        """
+        self.do_pop().show()
+
+    def do_thumbnail(self):
+        """usage: thumbnail <int:xsize> <int:ysize> <image:pic1>
+
+        Modify the top image in the stack to contain a thumbnail of itself.
+        """
+        ysize = int(self.do_pop())
+        xsize = int(self.do_pop())
+        self.top().thumbnail((xsize, ysize))
+
+    def do_transpose(self):
+        """usage: transpose <string:operator> <image:pic1>
+
+        Transpose the top image.
+        """
+        transpose = self.do_pop().upper()
+        image = self.do_pop()
+        self.push(image.transpose(transpose))
+
+    # Image attributes
+
+    def do_format(self):
+        """usage: format <image:pic1>
+
+        Push the format of the top image onto the stack.
+        """
+        self.push(self.do_pop().format)
+
+    def do_mode(self):
+        """usage: mode <image:pic1>
+
+        Push the mode of the top image onto the stack.
+        """
+        self.push(self.do_pop().mode)
+
+    def do_size(self):
+        """usage: size <image:pic1>
+
+        Push the image size on the stack as (y, x).
+        """
+        size = self.do_pop().size
+        self.push(size[0])
+        self.push(size[1])
+
+    # ImageChops operations
+
+    def do_invert(self):
+        """usage: invert <image:pic1>
+
+        Invert the top image.
+        """
+        from PIL import ImageChops
+        self.push(ImageChops.invert(self.do_pop()))
+
+    def do_lighter(self):
+        """usage: lighter <image:pic1> <image:pic2>
+
+        Pop the two top images, push an image of the lighter pixels of both.
+        """
+        from PIL import ImageChops
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        self.push(ImageChops.lighter(image1, image2))
+
+    def do_darker(self):
+        """usage: darker <image:pic1> <image:pic2>
+
+        Pop the two top images, push an image of the darker pixels of both.
+        """
+        from PIL import ImageChops
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        self.push(ImageChops.darker(image1, image2))
+
+    def do_difference(self):
+        """usage: difference <image:pic1> <image:pic2>
+
+        Pop the two top images, push the difference image
+        """
+        from PIL import ImageChops
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        self.push(ImageChops.difference(image1, image2))
+
+    def do_multiply(self):
+        """usage: multiply <image:pic1> <image:pic2>
+
+        Pop the two top images, push the multiplication image.
+        """
+        from PIL import ImageChops
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        self.push(ImageChops.multiply(image1, image2))
+
+    def do_screen(self):
+        """usage: screen <image:pic1> <image:pic2>
+
+        Pop the two top images, superimpose their inverted versions.
+        """
+        from PIL import ImageChops
+        image2 = self.do_pop()
+        image1 = self.do_pop()
+        self.push(ImageChops.screen(image1, image2))
+
+    def do_add(self):
+        """usage: add <image:pic1> <image:pic2> <int:offset> <float:scale>
+
+        Pop the two top images, produce the scaled sum with offset.
+        """
+        from PIL import ImageChops
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        scale = float(self.do_pop())
+        offset = int(self.do_pop())
+        self.push(ImageChops.add(image1, image2, scale, offset))
+
+    def do_subtract(self):
+        """usage: subtract <image:pic1> <image:pic2> <int:offset> <float:scale>
+
+        Pop the two top images, produce the scaled difference with offset.
+        """
+        from PIL import ImageChops
+        image1 = self.do_pop()
+        image2 = self.do_pop()
+        scale = float(self.do_pop())
+        offset = int(self.do_pop())
+        self.push(ImageChops.subtract(image1, image2, scale, offset))
+
+    # ImageEnhance classes
+
+    def do_color(self):
+        """usage: color <image:pic1>
+
+        Enhance color in the top image.
+        """
+        from PIL import ImageEnhance
+        factor = float(self.do_pop())
+        image = self.do_pop()
+        enhancer = ImageEnhance.Color(image)
+        self.push(enhancer.enhance(factor))
+
+    def do_contrast(self):
+        """usage: contrast <image:pic1>
+
+        Enhance contrast in the top image.
+        """
+        from PIL import ImageEnhance
+        factor = float(self.do_pop())
+        image = self.do_pop()
+        enhancer = ImageEnhance.Contrast(image)
+        self.push(enhancer.enhance(factor))
+
+    def do_brightness(self):
+        """usage: brightness <image:pic1>
+
+        Enhance brightness in the top image.
+        """
+        from PIL import ImageEnhance
+        factor = float(self.do_pop())
+        image = self.do_pop()
+        enhancer = ImageEnhance.Brightness(image)
+        self.push(enhancer.enhance(factor))
+
+    def do_sharpness(self):
+        """usage: sharpness <image:pic1>
+
+        Enhance sharpness in the top image.
+        """
+        from PIL import ImageEnhance
+        factor = float(self.do_pop())
+        image = self.do_pop()
+        enhancer = ImageEnhance.Sharpness(image)
+        self.push(enhancer.enhance(factor))
+
+    # The interpreter loop
+
+    def execute(self, list):
+        "Interpret a list of PILDriver commands."
+        list.reverse()
+        while len(list) > 0:
+            self.push(list[0])
+            list = list[1:]
+            if self.verbose:
+                print("Stack: " + repr(self.stack))
+            top = self.top()
+            if not isinstance(top, str):
+                continue
+            funcname = "do_" + top
+            if not hasattr(self, funcname):
+                continue
+            else:
+                self.do_pop()
+                func = getattr(self, funcname)
+                func()
+
+if __name__ == '__main__':
+    import sys
+
+    # If we see command-line arguments, interpret them as a stack state
+    # and execute.  Otherwise go interactive.
+
+    driver = PILDriver()
+    if len(sys.argv[1:]) > 0:
+        driver.execute(sys.argv[1:])
+    else:
+        print("PILDriver says hello.")
+        while True:
+            try:
+                if sys.version_info[0] >= 3:
+                    line = input('pildriver> ')
+                else:
+                    line = raw_input('pildriver> ')
+            except EOFError:
+                print("\nPILDriver says goodbye.")
+                break
+            driver.execute(line.split())
+            print(driver.stack)
+
+# The following sets edit modes for GNU EMACS
+# Local Variables:
+# mode:python
+# End:
diff --git a/stylelens/bin/pilfile.py b/stylelens/bin/pilfile.py
new file mode 100755
index 0000000..1772fec
--- /dev/null
+++ b/stylelens/bin/pilfile.py
@@ -0,0 +1,101 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library.
+# $Id$
+#
+# a utility to identify image files
+#
+# this script identifies image files, extracting size and
+# pixel mode information for known file formats.  Note that
+# you don't need the PIL C extension to use this module.
+#
+# History:
+# 0.0 1995-09-01 fl   Created
+# 0.1 1996-05-18 fl   Modified options, added debugging mode
+# 0.2 1996-12-29 fl   Added verify mode
+# 0.3 1999-06-05 fl   Don't mess up on class exceptions (1.5.2 and later)
+# 0.4 2003-09-30 fl   Expand wildcards on Windows; robustness tweaks
+#
+
+from __future__ import print_function
+
+import getopt
+import glob
+import logging
+import sys
+
+from PIL import Image
+
+if len(sys.argv) == 1:
+    print("PIL File 0.4/2003-09-30 -- identify image files")
+    print("Usage: pilfile [option] files...")
+    print("Options:")
+    print("  -f  list supported file formats")
+    print("  -i  show associated info and tile data")
+    print("  -v  verify file headers")
+    print("  -q  quiet, don't warn for unidentified/missing/broken files")
+    sys.exit(1)
+
+try:
+    opt, args = getopt.getopt(sys.argv[1:], "fqivD")
+except getopt.error as v:
+    print(v)
+    sys.exit(1)
+
+verbose = quiet = verify = 0
+logging_level = "WARNING"
+
+for o, a in opt:
+    if o == "-f":
+        Image.init()
+        id = sorted(Image.ID)
+        print("Supported formats:")
+        for i in id:
+            print(i, end=' ')
+        sys.exit(1)
+    elif o == "-i":
+        verbose = 1
+    elif o == "-q":
+        quiet = 1
+    elif o == "-v":
+        verify = 1
+    elif o == "-D":
+        logging_level = "DEBUG"
+
+logging.basicConfig(level=logging_level)
+
+
+def globfix(files):
+    # expand wildcards where necessary
+    if sys.platform == "win32":
+        out = []
+        for file in files:
+            if glob.has_magic(file):
+                out.extend(glob.glob(file))
+            else:
+                out.append(file)
+        return out
+    return files
+
+for file in globfix(args):
+    try:
+        im = Image.open(file)
+        print("%s:" % file, im.format, "%dx%d" % im.size, im.mode, end=' ')
+        if verbose:
+            print(im.info, im.tile, end=' ')
+        print()
+        if verify:
+            try:
+                im.verify()
+            except:
+                if not quiet:
+                    print("failed to verify image", end=' ')
+                    print("(%s:%s)" % (sys.exc_info()[0], sys.exc_info()[1]))
+    except IOError as v:
+        if not quiet:
+            print(file, "failed:", v)
+    except:
+        import traceback
+        if not quiet:
+            print(file, "failed:", "unexpected error")
+            traceback.print_exc(file=sys.stdout)
diff --git a/stylelens/bin/pilfont.py b/stylelens/bin/pilfont.py
new file mode 100755
index 0000000..9d40bd0
--- /dev/null
+++ b/stylelens/bin/pilfont.py
@@ -0,0 +1,57 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+# PIL raster font compiler
+#
+# history:
+# 1997-08-25 fl   created
+# 2002-03-10 fl   use "from PIL import"
+#
+
+from __future__ import print_function
+
+import glob
+import sys
+
+# drivers
+from PIL import BdfFontFile
+from PIL import PcfFontFile
+
+VERSION = "0.4"
+
+if len(sys.argv) <= 1:
+    print("PILFONT", VERSION, "-- PIL font compiler.")
+    print()
+    print("Usage: pilfont fontfiles...")
+    print()
+    print("Convert given font files to the PIL raster font format.")
+    print("This version of pilfont supports X BDF and PCF fonts.")
+    sys.exit(1)
+
+files = []
+for f in sys.argv[1:]:
+    files = files + glob.glob(f)
+
+for f in files:
+
+    print(f + "...", end=' ')
+
+    try:
+
+        fp = open(f, "rb")
+
+        try:
+            p = PcfFontFile.PcfFontFile(fp)
+        except SyntaxError:
+            fp.seek(0)
+            p = BdfFontFile.BdfFontFile(fp)
+
+        p.save(f)
+
+    except (SyntaxError, IOError):
+        print("failed")
+
+    else:
+        print("OK")
diff --git a/stylelens/bin/pilprint.py b/stylelens/bin/pilprint.py
new file mode 100755
index 0000000..35249fe
--- /dev/null
+++ b/stylelens/bin/pilprint.py
@@ -0,0 +1,102 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library.
+# $Id$
+#
+# print image files to postscript printer
+#
+# History:
+# 0.1   1996-04-20 fl   Created
+# 0.2   1996-10-04 fl   Use draft mode when converting.
+# 0.3   2003-05-06 fl   Fixed a typo or two.
+#
+
+from __future__ import print_function
+import getopt
+import os
+import sys
+import subprocess
+
+VERSION = "pilprint 0.3/2003-05-05"
+
+from PIL import Image
+from PIL import PSDraw
+
+letter = (1.0*72, 1.0*72, 7.5*72, 10.0*72)
+
+
+def description(filepath, image):
+    title = os.path.splitext(os.path.split(filepath)[1])[0]
+    format = " (%dx%d "
+    if image.format:
+        format = " (" + image.format + " %dx%d "
+    return title + format % image.size + image.mode + ")"
+
+if len(sys.argv) == 1:
+    print("PIL Print 0.3/2003-05-05 -- print image files")
+    print("Usage: pilprint files...")
+    print("Options:")
+    print("  -c            colour printer (default is monochrome)")
+    print("  -d            debug (show available drivers)")
+    print("  -p            print via lpr (default is stdout)")
+    print("  -P <printer>  same as -p but use given printer")
+    sys.exit(1)
+
+try:
+    opt, argv = getopt.getopt(sys.argv[1:], "cdpP:")
+except getopt.error as v:
+    print(v)
+    sys.exit(1)
+
+printerArgs = []  # print to stdout
+monochrome = 1    # reduce file size for most common case
+
+for o, a in opt:
+    if o == "-d":
+        # debug: show available drivers
+        Image.init()
+        print(Image.ID)
+        sys.exit(1)
+    elif o == "-c":
+        # colour printer
+        monochrome = 0
+    elif o == "-p":
+        # default printer channel
+        printerArgs = ["lpr"]
+    elif o == "-P":
+        # printer channel
+        printerArgs = ["lpr", "-P%s" % a]
+
+for filepath in argv:
+    try:
+
+        im = Image.open(filepath)
+
+        title = description(filepath, im)
+
+        if monochrome and im.mode not in ["1", "L"]:
+            im.draft("L", im.size)
+            im = im.convert("L")
+
+        if printerArgs:
+            p = subprocess.Popen(printerArgs, stdin=subprocess.PIPE)
+            fp = p.stdin
+        else:
+            fp = sys.stdout
+
+        ps = PSDraw.PSDraw(fp)
+
+        ps.begin_document()
+        ps.setfont("Helvetica-Narrow-Bold", 18)
+        ps.text((letter[0], letter[3]+24), title)
+        ps.setfont("Helvetica-Narrow-Bold", 8)
+        ps.text((letter[0], letter[1]-30), VERSION)
+        ps.image(letter, im)
+        ps.end_document()
+
+        if printerArgs:
+            fp.close()
+
+    except:
+        print("cannot print image", end=' ')
+        print("(%s:%s)" % (sys.exc_info()[0], sys.exc_info()[1]))
diff --git a/stylelens/bin/pip b/stylelens/bin/pip
new file mode 100755
index 0000000..d4a4455
--- /dev/null
+++ b/stylelens/bin/pip
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python3.6
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from pip import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/pip3 b/stylelens/bin/pip3
new file mode 100755
index 0000000..d4a4455
--- /dev/null
+++ b/stylelens/bin/pip3
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python3.6
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from pip import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/pip3.6 b/stylelens/bin/pip3.6
new file mode 100755
index 0000000..d4a4455
--- /dev/null
+++ b/stylelens/bin/pip3.6
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python3.6
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from pip import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/player.py b/stylelens/bin/player.py
new file mode 100755
index 0000000..88a1974
--- /dev/null
+++ b/stylelens/bin/player.py
@@ -0,0 +1,94 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+
+from __future__ import print_function
+
+import sys
+
+if sys.version_info[0] > 2:
+    import tkinter
+else:
+    import Tkinter as tkinter
+
+from PIL import Image, ImageTk
+
+
+# --------------------------------------------------------------------
+# an image animation player
+
+class UI(tkinter.Label):
+
+    def __init__(self, master, im):
+        self.im = im
+        if isinstance(self.im, list):
+            # list of images
+            im = self.im.pop(0)
+
+        if im.mode == "1":
+            self.image = ImageTk.BitmapImage(im, foreground="white")
+        else:
+            self.image = ImageTk.PhotoImage(im)
+
+        tkinter.Label.__init__(self, master, image=self.image, bg="black", bd=0)
+
+        self.update()
+
+        duration = im.info.get("duration", 100)
+        self.after(duration, self.next)
+
+    def next(self):
+
+        if isinstance(self.im, list):
+
+            try:
+                im = self.im[0]
+                del self.im[0]
+                self.image.paste(im)
+            except IndexError:
+                return  # end of list
+
+        else:
+
+            try:
+                im = self.im
+                im.seek(im.tell() + 1)
+                self.image.paste(im)
+            except EOFError:
+                return  # end of file
+
+        duration = im.info.get("duration", 100)
+        self.after(duration, self.next)
+
+        self.update_idletasks()
+
+
+# --------------------------------------------------------------------
+# script interface
+
+if __name__ == "__main__":
+
+    if not sys.argv[1:]:
+        print("Syntax: python player.py imagefile(s)")
+        sys.exit(1)
+
+    filename = sys.argv[1]
+
+    root = tkinter.Tk()
+    root.title(filename)
+
+    if len(sys.argv) > 2:
+        # list of images
+        print("loading...")
+        im = []
+        for filename in sys.argv[1:]:
+            im.append(Image.open(filename))
+    else:
+        # sequence
+        im = Image.open(filename)
+
+    UI(root, im).pack()
+
+    root.mainloop()
diff --git a/stylelens/bin/python b/stylelens/bin/python
new file mode 120000
index 0000000..039b719
--- /dev/null
+++ b/stylelens/bin/python
@@ -0,0 +1 @@
+python3.6
\ No newline at end of file
diff --git a/stylelens/bin/python-config b/stylelens/bin/python-config
new file mode 100755
index 0000000..3acd82e
--- /dev/null
+++ b/stylelens/bin/python-config
@@ -0,0 +1,78 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+import sys
+import getopt
+import sysconfig
+
+valid_opts = ['prefix', 'exec-prefix', 'includes', 'libs', 'cflags',
+              'ldflags', 'help']
+
+if sys.version_info >= (3, 2):
+    valid_opts.insert(-1, 'extension-suffix')
+    valid_opts.append('abiflags')
+if sys.version_info >= (3, 3):
+    valid_opts.append('configdir')
+
+
+def exit_with_usage(code=1):
+    sys.stderr.write("Usage: {0} [{1}]\n".format(
+        sys.argv[0], '|'.join('--'+opt for opt in valid_opts)))
+    sys.exit(code)
+
+try:
+    opts, args = getopt.getopt(sys.argv[1:], '', valid_opts)
+except getopt.error:
+    exit_with_usage()
+
+if not opts:
+    exit_with_usage()
+
+pyver = sysconfig.get_config_var('VERSION')
+getvar = sysconfig.get_config_var
+
+opt_flags = [flag for (flag, val) in opts]
+
+if '--help' in opt_flags:
+    exit_with_usage(code=0)
+
+for opt in opt_flags:
+    if opt == '--prefix':
+        print(sysconfig.get_config_var('prefix'))
+
+    elif opt == '--exec-prefix':
+        print(sysconfig.get_config_var('exec_prefix'))
+
+    elif opt in ('--includes', '--cflags'):
+        flags = ['-I' + sysconfig.get_path('include'),
+                 '-I' + sysconfig.get_path('platinclude')]
+        if opt == '--cflags':
+            flags.extend(getvar('CFLAGS').split())
+        print(' '.join(flags))
+
+    elif opt in ('--libs', '--ldflags'):
+        abiflags = getattr(sys, 'abiflags', '')
+        libs = ['-lpython' + pyver + abiflags]
+        libs += getvar('LIBS').split()
+        libs += getvar('SYSLIBS').split()
+        # add the prefix/lib/pythonX.Y/config dir, but only if there is no
+        # shared library in prefix/lib/.
+        if opt == '--ldflags':
+            if not getvar('Py_ENABLE_SHARED'):
+                libs.insert(0, '-L' + getvar('LIBPL'))
+            if not getvar('PYTHONFRAMEWORK'):
+                libs.extend(getvar('LINKFORSHARED').split())
+        print(' '.join(libs))
+
+    elif opt == '--extension-suffix':
+        ext_suffix = sysconfig.get_config_var('EXT_SUFFIX')
+        if ext_suffix is None:
+            ext_suffix = sysconfig.get_config_var('SO')
+        print(ext_suffix)
+
+    elif opt == '--abiflags':
+        if not getattr(sys, 'abiflags', None):
+            exit_with_usage()
+        print(sys.abiflags)
+
+    elif opt == '--configdir':
+        print(sysconfig.get_config_var('LIBPL'))
diff --git a/stylelens/bin/python3 b/stylelens/bin/python3
new file mode 120000
index 0000000..039b719
--- /dev/null
+++ b/stylelens/bin/python3
@@ -0,0 +1 @@
+python3.6
\ No newline at end of file
diff --git a/stylelens/bin/python3.6 b/stylelens/bin/python3.6
new file mode 100755
index 0000000..fb74bd1
Binary files /dev/null and b/stylelens/bin/python3.6 differ
diff --git a/stylelens/bin/rst2html.py b/stylelens/bin/rst2html.py
new file mode 100755
index 0000000..3544f64
--- /dev/null
+++ b/stylelens/bin/rst2html.py
@@ -0,0 +1,23 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2html.py 4564 2006-05-21 20:44:42Z wiemann $
+# Author: David Goodger <goodger@python.org>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing HTML.
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+
+
+description = ('Generates (X)HTML documents from standalone reStructuredText '
+               'sources.  ' + default_description)
+
+publish_cmdline(writer_name='html', description=description)
diff --git a/stylelens/bin/rst2html4.py b/stylelens/bin/rst2html4.py
new file mode 100755
index 0000000..0acd942
--- /dev/null
+++ b/stylelens/bin/rst2html4.py
@@ -0,0 +1,26 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2html4.py 7994 2016-12-10 17:41:45Z milde $
+# Author: David Goodger <goodger@python.org>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing (X)HTML.
+
+The output conforms to XHTML 1.0 transitional
+and almost to HTML 4.01 transitional (except for closing empty tags).
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+
+
+description = ('Generates (X)HTML documents from standalone reStructuredText '
+               'sources.  ' + default_description)
+
+publish_cmdline(writer_name='html4', description=description)
diff --git a/stylelens/bin/rst2html5.py b/stylelens/bin/rst2html5.py
new file mode 100755
index 0000000..e4b3e54
--- /dev/null
+++ b/stylelens/bin/rst2html5.py
@@ -0,0 +1,35 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+# -*- coding: utf8 -*-
+# :Copyright: © 2015 Günter Milde.
+# :License: Released under the terms of the `2-Clause BSD license`_, in short:
+#
+#    Copying and distribution of this file, with or without modification,
+#    are permitted in any medium without royalty provided the copyright
+#    notice and this notice are preserved.
+#    This file is offered as-is, without any warranty.
+#
+# .. _2-Clause BSD license: http://www.spdx.org/licenses/BSD-2-Clause
+#
+# Revision: $Revision: 7847 $
+# Date: $Date: 2015-03-17 18:30:47 +0100 (Di, 17 Mär 2015) $
+
+"""
+A minimal front end to the Docutils Publisher, producing HTML 5 documents.
+
+The output also conforms to XHTML 1.0 transitional
+(except for the doctype declaration).
+"""
+
+try:
+    import locale # module missing in Jython
+    locale.setlocale(locale.LC_ALL, '')
+except locale.Error:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+
+description = (u'Generates HTML 5 documents from standalone '
+               u'reStructuredText sources '
+               + default_description)
+
+publish_cmdline(writer_name='html5', description=description)
diff --git a/stylelens/bin/rst2latex.py b/stylelens/bin/rst2latex.py
new file mode 100755
index 0000000..423af10
--- /dev/null
+++ b/stylelens/bin/rst2latex.py
@@ -0,0 +1,26 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2latex.py 5905 2009-04-16 12:04:49Z milde $
+# Author: David Goodger <goodger@python.org>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing LaTeX.
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline
+
+description = ('Generates LaTeX documents from standalone reStructuredText '
+               'sources. '
+               'Reads from <source> (default is stdin) and writes to '
+               '<destination> (default is stdout).  See '
+               '<http://docutils.sourceforge.net/docs/user/latex.html> for '
+               'the full reference.')
+
+publish_cmdline(writer_name='latex', description=description)
diff --git a/stylelens/bin/rst2man.py b/stylelens/bin/rst2man.py
new file mode 100755
index 0000000..32e9768
--- /dev/null
+++ b/stylelens/bin/rst2man.py
@@ -0,0 +1,26 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# Author: 
+# Contact: grubert@users.sf.net
+# Copyright: This module has been placed in the public domain.
+
+"""
+man.py
+======
+
+This module provides a simple command line interface that uses the
+man page writer to output from ReStructuredText source.
+"""
+
+import locale
+try:
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+from docutils.writers import manpage
+
+description = ("Generates plain unix manual documents.  " + default_description)
+
+publish_cmdline(writer=manpage.Writer(), description=description)
diff --git a/stylelens/bin/rst2odt.py b/stylelens/bin/rst2odt.py
new file mode 100755
index 0000000..026b814
--- /dev/null
+++ b/stylelens/bin/rst2odt.py
@@ -0,0 +1,30 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2odt.py 5839 2009-01-07 19:09:28Z dkuhlman $
+# Author: Dave Kuhlman <dkuhlman@rexx.com>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A front end to the Docutils Publisher, producing OpenOffice documents.
+"""
+
+import sys
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline_to_binary, default_description
+from docutils.writers.odf_odt import Writer, Reader
+
+
+description = ('Generates OpenDocument/OpenOffice/ODF documents from '
+               'standalone reStructuredText sources.  ' + default_description)
+
+
+writer = Writer()
+reader = Reader()
+output = publish_cmdline_to_binary(reader=reader, writer=writer,
+    description=description)
+
diff --git a/stylelens/bin/rst2odt_prepstyles.py b/stylelens/bin/rst2odt_prepstyles.py
new file mode 100755
index 0000000..76ec91b
--- /dev/null
+++ b/stylelens/bin/rst2odt_prepstyles.py
@@ -0,0 +1,67 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2odt_prepstyles.py 5839 2009-01-07 19:09:28Z dkuhlman $
+# Author: Dave Kuhlman <dkuhlman@rexx.com>
+# Copyright: This module has been placed in the public domain.
+
+"""
+Fix a word-processor-generated styles.odt for odtwriter use: Drop page size
+specifications from styles.xml in STYLE_FILE.odt.
+"""
+
+#
+# Author: Michael Schutte <michi@uiae.at>
+
+from lxml import etree
+import sys
+import zipfile
+from tempfile import mkstemp
+import shutil
+import os
+
+NAMESPACES = {
+    "style": "urn:oasis:names:tc:opendocument:xmlns:style:1.0",
+    "fo": "urn:oasis:names:tc:opendocument:xmlns:xsl-fo-compatible:1.0"
+}
+
+def prepstyle(filename):
+    
+    zin = zipfile.ZipFile(filename)
+    styles = zin.read("styles.xml")
+    
+    root = etree.fromstring(styles)
+    for el in root.xpath("//style:page-layout-properties", 
+        namespaces=NAMESPACES):
+        for attr in el.attrib:
+            if attr.startswith("{%s}" % NAMESPACES["fo"]):
+                del el.attrib[attr]
+    
+    tempname = mkstemp()
+    zout = zipfile.ZipFile(os.fdopen(tempname[0], "w"), "w",
+        zipfile.ZIP_DEFLATED)
+    
+    for item in zin.infolist():
+        if item.filename == "styles.xml":
+            zout.writestr(item, etree.tostring(root))
+        else:
+            zout.writestr(item, zin.read(item.filename))
+    
+    zout.close()
+    zin.close()
+    shutil.move(tempname[1], filename)
+
+
+def main():
+    args = sys.argv[1:]
+    if len(args) != 1:
+        print >> sys.stderr, __doc__
+        print >> sys.stderr, "Usage: %s STYLE_FILE.odt\n" % sys.argv[0]
+        sys.exit(1)
+    filename = args[0]
+    prepstyle(filename)
+
+if __name__ == '__main__':
+    main()
+
+
+# vim:tw=78:sw=4:sts=4:et:
diff --git a/stylelens/bin/rst2pseudoxml.py b/stylelens/bin/rst2pseudoxml.py
new file mode 100755
index 0000000..ee511c9
--- /dev/null
+++ b/stylelens/bin/rst2pseudoxml.py
@@ -0,0 +1,23 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2pseudoxml.py 4564 2006-05-21 20:44:42Z wiemann $
+# Author: David Goodger <goodger@python.org>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing pseudo-XML.
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+
+
+description = ('Generates pseudo-XML from standalone reStructuredText '
+               'sources (for testing purposes).  ' + default_description)
+
+publish_cmdline(description=description)
diff --git a/stylelens/bin/rst2s5.py b/stylelens/bin/rst2s5.py
new file mode 100755
index 0000000..c95a7e0
--- /dev/null
+++ b/stylelens/bin/rst2s5.py
@@ -0,0 +1,24 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2s5.py 4564 2006-05-21 20:44:42Z wiemann $
+# Author: Chris Liechti <cliechti@gmx.net>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing HTML slides using
+the S5 template system.
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+
+
+description = ('Generates S5 (X)HTML slideshow documents from standalone '
+               'reStructuredText sources.  ' + default_description)
+
+publish_cmdline(writer_name='s5', description=description)
diff --git a/stylelens/bin/rst2xetex.py b/stylelens/bin/rst2xetex.py
new file mode 100755
index 0000000..8f91789
--- /dev/null
+++ b/stylelens/bin/rst2xetex.py
@@ -0,0 +1,27 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2xetex.py 7847 2015-03-17 17:30:47Z milde $
+# Author: Guenter Milde
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing Lua/XeLaTeX code.
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline
+
+description = ('Generates LaTeX documents from standalone reStructuredText '
+               'sources for compilation with the Unicode-aware TeX variants '
+               'XeLaTeX or LuaLaTeX. '
+               'Reads from <source> (default is stdin) and writes to '
+               '<destination> (default is stdout).  See '
+               '<http://docutils.sourceforge.net/docs/user/latex.html> for '
+               'the full reference.')
+
+publish_cmdline(writer_name='xetex', description=description)
diff --git a/stylelens/bin/rst2xml.py b/stylelens/bin/rst2xml.py
new file mode 100755
index 0000000..6c84af5
--- /dev/null
+++ b/stylelens/bin/rst2xml.py
@@ -0,0 +1,23 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rst2xml.py 4564 2006-05-21 20:44:42Z wiemann $
+# Author: David Goodger <goodger@python.org>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing Docutils XML.
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+
+
+description = ('Generates Docutils-native XML from standalone '
+               'reStructuredText sources.  ' + default_description)
+
+publish_cmdline(writer_name='xml', description=description)
diff --git a/stylelens/bin/rstpep2html.py b/stylelens/bin/rstpep2html.py
new file mode 100755
index 0000000..df99388
--- /dev/null
+++ b/stylelens/bin/rstpep2html.py
@@ -0,0 +1,25 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# $Id: rstpep2html.py 4564 2006-05-21 20:44:42Z wiemann $
+# Author: David Goodger <goodger@python.org>
+# Copyright: This module has been placed in the public domain.
+
+"""
+A minimal front end to the Docutils Publisher, producing HTML from PEP
+(Python Enhancement Proposal) documents.
+"""
+
+try:
+    import locale
+    locale.setlocale(locale.LC_ALL, '')
+except:
+    pass
+
+from docutils.core import publish_cmdline, default_description
+
+
+description = ('Generates (X)HTML from reStructuredText-format PEP files.  '
+               + default_description)
+
+publish_cmdline(reader_name='pep', writer_name='pep_html',
+                description=description)
diff --git a/stylelens/bin/saved_model_cli b/stylelens/bin/saved_model_cli
new file mode 100755
index 0000000..5fb2816
--- /dev/null
+++ b/stylelens/bin/saved_model_cli
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from tensorflow.python.tools.saved_model_cli import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/tensorboard b/stylelens/bin/tensorboard
new file mode 100755
index 0000000..10a1c3f
--- /dev/null
+++ b/stylelens/bin/tensorboard
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from tensorboard.main import run_main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(run_main())
diff --git a/stylelens/bin/thresholder.py b/stylelens/bin/thresholder.py
new file mode 100755
index 0000000..904229c
--- /dev/null
+++ b/stylelens/bin/thresholder.py
@@ -0,0 +1,80 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+# this demo script illustrates how a 1-bit BitmapImage can be used
+# as a dynamically updated overlay
+#
+
+import sys
+
+if sys.version_info[0] > 2:
+    import tkinter
+else:
+    import Tkinter as tkinter
+
+from PIL import Image, ImageTk
+
+#
+# an image viewer
+
+
+class UI(tkinter.Frame):
+    def __init__(self, master, im, value=128):
+        tkinter.Frame.__init__(self, master)
+
+        self.image = im
+        self.value = value
+
+        self.canvas = tkinter.Canvas(self, width=im.size[0], height=im.size[1])
+        self.backdrop = ImageTk.PhotoImage(im)
+        self.canvas.create_image(0, 0, image=self.backdrop, anchor=tkinter.NW)
+        self.canvas.pack()
+
+        scale = tkinter.Scale(self, orient=tkinter.HORIZONTAL, from_=0, to=255,
+                              resolution=1, command=self.update_scale,
+                              length=256)
+        scale.set(value)
+        scale.bind("<ButtonRelease-1>", self.redraw)
+        scale.pack()
+
+        # uncomment the following line for instant feedback (might
+        # be too slow on some platforms)
+        # self.redraw()
+
+    def update_scale(self, value):
+        self.value = float(value)
+
+        self.redraw()
+
+    def redraw(self, event=None):
+
+        # create overlay (note the explicit conversion to mode "1")
+        im = self.image.point(lambda v, t=self.value: v >= t, "1")
+        self.overlay = ImageTk.BitmapImage(im, foreground="green")
+
+        # update canvas
+        self.canvas.delete("overlay")
+        self.canvas.create_image(0, 0, image=self.overlay, anchor=tkinter.NW,
+                                 tags="overlay")
+
+# --------------------------------------------------------------------
+# main
+
+if len(sys.argv) != 2:
+    print("Usage: thresholder file")
+    sys.exit(1)
+
+root = tkinter.Tk()
+
+im = Image.open(sys.argv[1])
+
+if im.mode != "L":
+    im = im.convert("L")
+
+# im.thumbnail((320,200))
+
+UI(root, im).pack()
+
+root.mainloop()
diff --git a/stylelens/bin/toco b/stylelens/bin/toco
new file mode 100755
index 0000000..16d811d
--- /dev/null
+++ b/stylelens/bin/toco
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from tensorflow.contrib.lite.toco.python.toco_wrapper import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/toco_from_protos b/stylelens/bin/toco_from_protos
new file mode 100755
index 0000000..47a09bf
--- /dev/null
+++ b/stylelens/bin/toco_from_protos
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from tensorflow.contrib.lite.toco.python.toco_from_protos import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/bin/viewer.py b/stylelens/bin/viewer.py
new file mode 100755
index 0000000..139dd3b
--- /dev/null
+++ b/stylelens/bin/viewer.py
@@ -0,0 +1,55 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python
+#
+# The Python Imaging Library
+# $Id$
+#
+
+from __future__ import print_function
+
+import sys
+
+if sys.version_info[0] > 2:
+    import tkinter
+else:
+    import Tkinter as tkinter
+
+from PIL import Image, ImageTk
+
+#
+# an image viewer
+
+
+class UI(tkinter.Label):
+
+    def __init__(self, master, im):
+
+        if im.mode == "1":
+            # bitmap image
+            self.image = ImageTk.BitmapImage(im, foreground="white")
+            tkinter.Label.__init__(self, master, image=self.image, bd=0,
+                                   bg="black")
+
+        else:
+            # photo image
+            self.image = ImageTk.PhotoImage(im)
+            tkinter.Label.__init__(self, master, image=self.image, bd=0)
+
+#
+# script interface
+
+if __name__ == "__main__":
+
+    if not sys.argv[1:]:
+        print("Syntax: python viewer.py imagefile")
+        sys.exit(1)
+
+    filename = sys.argv[1]
+
+    root = tkinter.Tk()
+    root.title(filename)
+
+    im = Image.open(filename)
+
+    UI(root, im).pack()
+
+    root.mainloop()
diff --git a/stylelens/bin/wheel b/stylelens/bin/wheel
new file mode 100755
index 0000000..e98fb2a
--- /dev/null
+++ b/stylelens/bin/wheel
@@ -0,0 +1,11 @@
+#!/Users/lion/PycharmProjects/bl-detect/stylelens/bin/python3.6
+
+# -*- coding: utf-8 -*-
+import re
+import sys
+
+from wheel.tool import main
+
+if __name__ == '__main__':
+    sys.argv[0] = re.sub(r'(-script\.pyw?|\.exe)?$', '', sys.argv[0])
+    sys.exit(main())
diff --git a/stylelens/include/python3.6m b/stylelens/include/python3.6m
new file mode 120000
index 0000000..a0f3e18
--- /dev/null
+++ b/stylelens/include/python3.6m
@@ -0,0 +1 @@
+/Library/Frameworks/Python.framework/Versions/3.6/include/python3.6m
\ No newline at end of file
diff --git a/stylelens/pip-selfcheck.json b/stylelens/pip-selfcheck.json
new file mode 100644
index 0000000..49a7097
--- /dev/null
+++ b/stylelens/pip-selfcheck.json
@@ -0,0 +1 @@
+{"last_check":"2018-04-12T08:46:52Z","pypi_version":"9.0.3"}
\ No newline at end of file