Pull frontend

back/src/controller.py

@@ -7,42 +7,120 @@
 from audio import AudioSignal
 from stft import Stft
 from spectrogram import Spectrogram
-from routes import musics
+from routes import musics, allowed_file
 from app import create_app
+import os
+from flask import current_app,jsonify,request,flash, redirect, url_for
+from app import create_app,db, UPLOAD_FOLDER, ALLOWED_EXTENSIONS
+from models import Musics,musics_schema,Images,images_schema
+from werkzeug.utils import secure_filename
+from tinytag import TinyTag
+import numpy as np
 
 # app = Flask("SpectrogramAPI")
 app = create_app()
 api = Api(app)
 
+app.secret_key = 'bcyiae7doqbucmopighyi'
+
 class Generate_spectrogram(Resource):
+
     def post(self):
 
         json_dict = request.get_json(force=True)
         parameters = StftParams().set_by_json(json_dict)
 
-        audio_id = json_dict["specId"]
+        audio_id = json_dict["specid"]
         print(audio_id)
 
-        print("#########################")
         musics = Musics.query.filter_by(id=audio_id)
         audio_file_path = musics_schema.dump(musics)[0]["path"]
 
         audio = AudioSignal(audio_file_path=audio_file_path)
 
         stft = Stft(parameters).set_stft_from_audio(audio)
+        stft.set_spectral_maxima()
 
         spectrogram = Spectrogram(stft)
         b64_img = spectrogram.visualize()
 
-        data = {}
-        data['id'] = '1'
-        data['image'] = str(b64_img)
-
-        json_response = json.dumps(data)
+        img = str(b64_img, "utf-8")
 
-        return json_response
+        return img
 
 api.add_resource(Generate_spectrogram, "/genspec")
 
+@app.route("/uploadfile", methods=["GET","POST"], strict_slashes=False)
+def musics_post():
+    if request.method == "POST":
+        print(request.files)
+        if 'file' not in request.files:
+            flash('No file part')
+            return redirect(request.url)
+
+        file = request.files['file']
+        # If the user does not select a file, the browser submits an
+        # empty file without a filename.
+        if file.filename == '':
+            flash('No selected file')
+            return redirect(request.url)
+
+        path = app.config['UPLOAD_FOLDER']+ '/' + file.filename
+
+        if file and allowed_file(file.filename):
+            filename = secure_filename(file.filename)
+            file.save(os.path.join(app.config['UPLOAD_FOLDER'], filename))
+
+        music_file = TinyTag.get(path)
+        name = file.filename
+        if music_file.title:
+            name = music_file.title
+        artist = music_file.artist
+        new_music = Musics(music=name, artist=artist, path=path)
+        db.session.add(new_music)
+        db.session.commit()
+
+    musics = Musics.query.all()
+    results = musics_schema.dump(musics)
+    return jsonify(results)
+
+@app.route("/deletefile", methods=["GET", "POST"], strict_slashes=False)
+def music_delete():
+
+    if 'id' not in request.form:
+        flash('Without id')
+        return redirect(request.url)
+
+    json_dict = request.get_json(force=True)
+
+    deleting_id = json_dict["specid"]
+
+    music = Musics.query.filter_by(id=deleting_id).first()
+
+    if os.path.exists(music.path):
+        os.remove(music.path)
+
+    db.session.delete(music)
+    db.session.commit()
+
+@app.route("/deleteall", methods=["GET", "DELETE"], strict_slashes=False)
+def music_delete_all():
+
+    musics = Musics.query.all()
+
+    results = musics_schema.dump(musics)
+
+    print(results)
+
+    paths = [res["path"] for res in results]
+
+    for path in paths:
+        if os.path.exists(path):
+            print("##########")
+            print(f"os.remove({path})")
+
+    db.session.delete(musics)
+    db.session.commit()
+
 if __name__ == "__main__":
     app.run(port=8080, debug=True)

back/src/parameters.py

@@ -3,6 +3,7 @@ class StftParams:
 
     def __init__(self, frame_size=1024, hop_length=512, window="hann",
                  mode="power", cmap="prism", sr=None, db=True, freq_slice=None):
+
         self.mode = mode
         self.window = window
         self.frame_size = frame_size
@@ -13,9 +14,12 @@ def __init__(self, frame_size=1024, hop_length=512, window="hann",
         self.freq_slice = freq_slice
 
     def set_by_json(self, json_dict):
+        self.db = json_dict["intensity"]
+        self.analysis = json_dict["analysis"]
         self.mode = json_dict["mode"]
         self.window = json_dict["window"]
         self.frame_size = json_dict["framelength"]
         self.hop_length = json_dict["hoplength"]
         self.cmap = json_dict["cmap"]
+
         return self

back/src/routes.py

@@ -27,9 +27,10 @@ def musics():
     #path = np.array(results)[idxs]['path']
     return (jsonify(results))
 
-@app.route("/musics-post", methods=["GET","POST"], strict_slashes=False)
+@app.route("/uploadfile", methods=["GET","POST"], strict_slashes=False)
 def musics_post():
 	if request.method == "POST":
+		print(request)
 		if 'file' not in request.files:
 			flash('No file part')
 			return redirect(request.url)

back/src/spectrogram.py

@@ -1,12 +1,12 @@
 import numpy as np
 import matplotlib.pyplot as plt
 from librosa import display as ld
+import librosa as rosa
 from abc import ABC, abstractmethod
 import copy
 import io
 import base64
 
-
 class VisualizationStrategy(ABC):
 
     @abstractmethod
@@ -25,34 +25,40 @@ def visualize(self, stft, cmap=None):
                     y_axis="linear")
 
         bytes_string = io.BytesIO()
-        plt.savefig(bytes_string, format='png', dpi=1800)
+        plt.savefig(bytes_string, format='png', dpi=1800, bbox_inches="tight",
+                    pad_inches=0)
+
         bytes_string.seek(0)
         b64_img = base64.b64encode(bytes_string.read())
 
         plt.close()
 
         return b64_img
 
-
 class MatplotVisualizationStrategy(VisualizationStrategy):
 
     def visualize(self, stft, cmap):
 
         plt.imshow(stft.fft_frames, cmap=cmap)
+
+        if stft.analysis == "complex":
+            plt.plot(stft.spectral_maxima, color="red", linewidth=0.1)
+
         plt.xlabel("")
         plt.ylabel("")
         plt.xticks([])
         plt.yticks([])
 
         bytes_string = io.BytesIO()
-        plt.savefig(bytes_string, format='png', dpi=1800)
+        plt.savefig(bytes_string, format='png', dpi=1800, bbox_inches="tight",
+                    pad_inches=0, transparent=True)
+
         bytes_string.seek(0)
         b64_img = base64.b64encode(bytes_string.read())
 
         plt.close()
         return b64_img
 
-
 class Spectrogram():
 
     def __init__(self, stft):
@@ -81,4 +87,3 @@ def set_strategy(self, strategy="rosa"):
     def visualize(self):
         img = self.visualizer.visualize(self.stft, self.cmap)
         return img
-

back/src/stft.py

@@ -16,9 +16,13 @@ def __init__(self, parameters):
         self.sr = parameters.sr
         self.db = parameters.db
         self.freq_slice = parameters.freq_slice
+        self.analysis = parameters.analysis
+        self.spectral_maxima = None
 
     def set_stft(self, signal):
 
+        assert self.frame_size > self.hop_length, "Tamanho de salto inferior a tamanho de quadro de FFT"
+
         mode_transform = {
                            "power": np.abs,
                            "abs": np.abs,
@@ -36,9 +40,9 @@ def set_stft(self, signal):
                                                      nperseg=self.frame_size,
                                                      noverlap=self.hop_length)
 
-        fft_frames = rosa.stft(signal, n_fft=self.frame_size,
-                               hop_length=self.hop_length,
-                               window=self.window)
+        # fft_frames = rosa.stft(signal, n_fft=self.frame_size,
+        #                        hop_length=self.hop_length,
+        #                        window=self.window)
 
         if self.freq_slice is not None:
             fft_frames = fft_frames[self.freq_slice]
@@ -48,7 +52,10 @@ def set_stft(self, signal):
         if self.mode == "power":
             fft_frames = np.square(fft_frames)
 
-        if self.db:
+        if self.db == "db":
+            fft_frames = rosa.amplitude_to_db(fft_frames, ref=np.max)
+        else:
+            fft_frames[np.where(fft_frames <= 0)] = 1e-12
             fft_frames = 10*np.log10(fft_frames)
 
         fft_frames = np.flip(fft_frames, axis=0)
@@ -60,9 +67,24 @@ def set_stft_from_audio(self, audio_signal):
         self.sr = audio_signal.sr
 
         self.set_stft(audio_signal.signal)
+
         return self
 
     def get_stft(self):
+
         assert self.fft_frames is not None, "SFTF data not defined"
 
         return self.fft_frames
+
+    # def get_frame_maxima(self, fft_frame, n=1):
+
+    #     return np.mean(np.argpartition(fft_frame, -n)[-n:])
+
+    def set_spectral_maxima(self, stft_params=1, n=1):
+
+        maxima = np.zeros(self.fft_frames.shape[1])
+
+        for f, frame in enumerate(self.fft_frames.T):
+            maxima[f] = np.argpartition(frame, -1)[-1]
+
+        self.spectral_maxima = maxima

back/test/spectrogram.py

@@ -6,6 +6,8 @@
 import io
 import base64
 
+mpl.rcParams['savefig.pad_inches'] = 0
+
 class VisualizationStrategy(ABC):
 
     @abstractmethod
@@ -24,15 +26,15 @@ def visualize(self, stft, cmap=None):
                     y_axis="linear")
 
         bytes_string = io.BytesIO()
-        plt.savefig(bytes_string, format='png')
+        plt.autoscale(tight=True)
+        plt.savefig(bytes_string, format='png', bbox_inches="tight")
         bytes_string.seek(0)
         b64_img = base64.b64encode(bytes_string.read())
 
         plt.close()
 
         return b64_img
 
-
 class MatplotVisualizationStrategy(VisualizationStrategy):
 
     def visualize(self, stft, cmap):
@@ -44,14 +46,16 @@ def visualize(self, stft, cmap):
         plt.yticks([])
 
         bytes_string = io.BytesIO()
-        plt.savefig(bytes_string, format='png')
+        plt.autoscale(tight=True)
+        plt.margins(x=0)
+        plt.margins(y=0)
+        plt.savefig(bytes_string, format='png', bbox_inches="tight")
         bytes_string.seek(0)
         b64_img = base64.b64encode(bytes_string.read())
 
         plt.close()
         return b64_img
 
-
 class Spectrogram():
 
     def __init__(self, stft):

back/test/stft.py

@@ -49,7 +49,7 @@ def set_stft(self, signal):
             fft_frames = np.square(fft_frames)
 
         if self.db:
-            fft_frames = 10*np.log10(fft_frames)
+            fft_frames = librosa.amplitude_to_db(fft_frames, ref=np.max)
 
         fft_frames = np.flip(fft_frames, axis=0)