[WIP] Fix mediapipe execution and example documentation

08.OpenCV-Mediapipe-DEMO/app-hands.py

@@ -2,7 +2,7 @@
 import mediapipe as mp
 import time
 
-cap = cv2.VideoCapture(1)
+cap = cv2.VideoCapture(0)
 mpHands = mp.solutions.hands
 
 hands = mpHands.Hands(min_detection_confidence=0.5, min_tracking_confidence=0.5)
@@ -42,5 +42,8 @@
 
         cv2.imshow('img', img)
 
-    if cv2.waitKey(1) == ord('q'):
-        break
+    if cv2.waitKey(1) == ord('q') or cv2.waitKey(1) == 27:
+        break
+
+cap.release()
+cv2.destroyAllWindows()

08.OpenCV-Mediapipe-DEMO/app-holistic.py

@@ -1,12 +1,14 @@
 import cv2
 import mediapipe as mp
+import numpy as np
 
 mp_drawing = mp.solutions.drawing_utils
 mp_drawing_styles = mp.solutions.drawing_styles
 mp_holistic = mp.solutions.holistic
 
 # For static images:
 IMAGE_FILES = []
+BG_COLOR = (192, 192, 192) # gray
 with mp_holistic.Holistic(
     static_image_mode=True,
     model_complexity=2,
@@ -53,7 +55,7 @@
         results.pose_world_landmarks, mp_holistic.POSE_CONNECTIONS)
 
 # For webcam input:
-cap = cv2.VideoCapture(1)
+cap = cv2.VideoCapture(0)
 with mp_holistic.Holistic(
     min_detection_confidence=0.5,
     min_tracking_confidence=0.5) as holistic:
@@ -88,6 +90,7 @@
         .get_default_pose_landmarks_style())
     # Flip the image horizontally for a selfie-view display.
     cv2.imshow('MediaPipe Holistic', cv2.flip(image, 1))
-    if cv2.waitKey(5) & 0xFF == 27:
+    if cv2.waitKey(5) & 0xFF == 27 or cv2.waitKey(5) == ord('q'):
       break
-cap.release()
+cap.release()
+cv2.destroyAllWindows()

08.OpenCV-Mediapipe-DEMO/app-pose.py

@@ -1,5 +1,7 @@
 import cv2
 import mediapipe as mp
+import numpy as np
+
 mp_drawing = mp.solutions.drawing_utils
 mp_drawing_styles = mp.solutions.drawing_styles
 mp_pose = mp.solutions.pose
@@ -46,7 +48,7 @@
         results.pose_world_landmarks, mp_pose.POSE_CONNECTIONS)
 
 # For webcam input:
-cap = cv2.VideoCapture(1)
+cap = cv2.VideoCapture(0)
 with mp_pose.Pose(
     min_detection_confidence=0.5,
     min_tracking_confidence=0.5) as pose:
@@ -73,6 +75,7 @@
         landmark_drawing_spec=mp_drawing_styles.get_default_pose_landmarks_style())
     # Flip the image horizontally for a selfie-view display.
     cv2.imshow('MediaPipe Pose', cv2.flip(image, 1))
-    if cv2.waitKey(5) & 0xFF == 27:
+    if cv2.waitKey(5) & 0xFF == 27 or cv2.waitKey(5) == ord('q'):
       break
-cap.release()
+cap.release()
+cv2.destroyAllWindows()

08.OpenCV-Mediapipe-DEMO/handle-hand-demo.py

@@ -140,9 +140,10 @@ def detect():
                             center_y = int(keypoint_pos[node][1])
                             frame = mosaic(frame, [center_x - 15 , center_y - 10], [center_x + 30, center_y + 50])
         cv2.imshow('MediaPipe Hands', frame)
-        if cv2.waitKey(1) & 0xFF == 27:
+        if cv2.waitKey(1) & 0xFF == 27 or cv2.waitKey(1) == ord('q'):
             break
     cap.release()
+    cv2.destroyAllWindows()
 
 if __name__ == '__main__':
     detect()

08.OpenCV-Mediapipe-DEMO/readme.md

@@ -4,11 +4,11 @@
 
 
 ## OpenCV + MediaPipe
-- 建議使用pipenv虛擬環境，本案例採python 3.8，相依外部套件可透過`pipenv sync`將`Pipfile.lock`內鎖定的相依套件進行安裝。
+- 建議使用pipenv虛擬環境，本案例採python 3.10以上，相依外部套件可透過`pipenv install`安裝所需套件。
 
     ```
     pipenv --python 3.10
-    pipenv sync
+    pipenv install
     ```
 
 - pipenv相關命令:
@@ -20,14 +20,20 @@
 
 
 - 執行程式: 
-  `pipenv shell` 進入虛擬環境後，選擇自己想執行的程式開啟，開啟後按`esc`或`q`離開。
+  `pipenv shell` 進入虛擬環境後，選擇自己想執行的程式開啟，開啟後按`ESC`或`q`離開。
 
-    ```
+    ```bash
     python app-hands.py  #手部辨識
     python app-holistic.py  #肢體辨識
     python app-pose.py  #姿態辨識
+    python handle-hand-demo.py  #手勢辨識(愛心/中指)
     ```
 
+- 注意事項:
+  - 程式預設使用編號0的攝影機(通常是主要攝影機)
+  - 如果有多個攝影機，可以在程式碼中修改`cv2.VideoCapture(0)`的數字
+  - 執行時需要允許程式存取攝影機權限
+
 
 
 ## 參考: