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008 OpenCV MediaPipe Hands Detection
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‎008_OpenCV_MediaPipe_hand_detection.md

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# OpenCV Capture Camera Video
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Use OpenCV and MediaPipe to detect hands.
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https://google.github.io/mediapipe/solutions/hands
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## Requirements
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1. It'll open the computer's camera and show the video in a window.
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2. When hands show in the video, it'll draw the hands landmarks.
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3. When you press "q" key it'll quit.
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## What will we practice in this project?
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- OpenCV: you need to install the `opencv-python` package via `pip install opencv-python` command in this project environment.
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- while loop
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- MediaPipe hands solution
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## A reference code
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### handUtils.py
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```python
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import cv2
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import mediapipe as mp
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class HandDetector():
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def __init__(self):
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self.hand_detector = mp.solutions.hands.Hands()
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self.drawer = mp.solutions.drawing_utils
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def process(self, img, draw=True):
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img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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self.hands_data = self.hand_detector.process(img_rgb)
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if draw:
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if self.hands_data.multi_hand_landmarks:
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for handlms in self.hands_data.multi_hand_landmarks:
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self.drawer.draw_landmarks(img, handlms, mp.solutions.hands.HAND_CONNECTIONS)
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def find_position(self, img):
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h, w, c = img.shape
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position = {'Left': {}, 'Right': {}}
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if self.hands_data.multi_hand_landmarks:
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i = 0
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for point in self.hands_data.multi_handedness:
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score = point.classification[0].score
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if score >= 0.8:
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label = point.classification[0].label
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hand_lms = self.hands_data.multi_hand_landmarks[i].landmark
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for id, lm in enumerate(hand_lms):
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x, y = int(lm.x * w), int(lm.y * h)
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position[label][id] = (x, y)
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i = i + 1
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return position
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```
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### hand.py
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```python
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import cv2
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from handUtils import HandDetector
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camera = cv2.VideoCapture(1)
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hand_detector = HandDetector()
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while True:
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success, img = camera.read()
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if success:
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img = cv2.flip(img, 1)
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hand_detector.process(img, draw=False)
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position = hand_detector.find_position(img)
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left_finger = position['Left'].get(8, None)
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if left_finger:
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cv2.circle(img, (left_finger[0], left_finger[1]),10, (0, 0, 255), cv2.FILLED)
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right_finger = position['Right'].get(8, None)
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if right_finger:
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cv2.circle(img, (right_finger[0], right_finger[1]),10, (0, 255, 0), cv2.FILLED)
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cv2.imshow('Video', img)
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k = cv2.waitKey(1)
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if k == ord('q'):
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break
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camera.release()
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cv2.destroyAllWindows()
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```
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## Run the demo
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Install the OpenCV & MediaPipe:
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```shell
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pip install opencv-python mediapipe
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```
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Please save the 2 Python files and run it：
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```
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python hand.py
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```
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----
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# 使用OpenCV和MediaPipe进行手势识别
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## 项目需求
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- 运行程序会打开电脑摄像头，并显示捕捉到的视频
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- 如果视频中出现了手，则显示手势连线
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- 按`q`键会退出程序
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## 项目练习
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- 安装OpenCV，需要使用`pip install opencv-python mediapipe`将OpenCV和MediaPipe安装到项目环境中
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- MediaPipe手势识别：https://google.github.io/mediapipe/solutions/hands
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## 项目参考代码
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### handUtils.py
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```python
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import cv2
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import mediapipe as mp
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class HandDetector():
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def __init__(self):
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self.hand_detector = mp.solutions.hands.Hands()
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self.drawer = mp.solutions.drawing_utils
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def process(self, img, draw=True):
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img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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self.hands_data = self.hand_detector.process(img_rgb)
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if draw:
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if self.hands_data.multi_hand_landmarks:
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for handlms in self.hands_data.multi_hand_landmarks:
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self.drawer.draw_landmarks(img, handlms, mp.solutions.hands.HAND_CONNECTIONS)
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def find_position(self, img):
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h, w, c = img.shape
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position = {'Left': {}, 'Right': {}}
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if self.hands_data.multi_hand_landmarks:
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i = 0
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for point in self.hands_data.multi_handedness:
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score = point.classification[0].score
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if score >= 0.8:
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label = point.classification[0].label
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hand_lms = self.hands_data.multi_hand_landmarks[i].landmark
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for id, lm in enumerate(hand_lms):
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x, y = int(lm.x * w), int(lm.y * h)
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position[label][id] = (x, y)
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i = i + 1
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return position
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```
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### hand.py
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```python
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import cv2
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from handUtils import HandDetector
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camera = cv2.VideoCapture(1)
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hand_detector = HandDetector()
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while True:
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success, img = camera.read()
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if success:
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img = cv2.flip(img, 1)
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hand_detector.process(img, draw=False)
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position = hand_detector.find_position(img)
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left_finger = position['Left'].get(8, None)
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if left_finger:
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cv2.circle(img, (left_finger[0], left_finger[1]),10, (0, 0, 255), cv2.FILLED)
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right_finger = position['Right'].get(8, None)
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if right_finger:
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cv2.circle(img, (right_finger[0], right_finger[1]),10, (0, 255, 0), cv2.FILLED)
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cv2.imshow('Video', img)
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k = cv2.waitKey(1)
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if k == ord('q'):
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break
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camera.release()
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cv2.destroyAllWindows()
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```
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## 测试运行
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Install OpenCV and MediaPipe:
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```shell
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pip install opencv-python mediapipe
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```
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保存上面2个代码并运行：
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```
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python hand.py
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```

‎README.md

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## 007 OpenCV Capture Camera Video
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https://github.com/zhiwehu/100_plus_Python_Projects_Challenge/blob/main/007_OpenCV_Capture_Camera_Video.md
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https://github.com/zhiwehu/100_plus_Python_Projects_Challenge/blob/main/007_OpenCV_Capture_Camera_Video.md
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## 008 OpenCV MediaPipe Hands Detection
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https://github.com/zhiwehu/100_plus_Python_Projects_Challenge/blob/main/008_OpenCV_MediaPipe_hand_detection.md

‎code/8/hand.py

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import cv2
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from handUtils import HandDetector
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camera = cv2.VideoCapture(1)
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hand_detector = HandDetector()
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while True:
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success, img = camera.read()
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if success:
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img = cv2.flip(img, 1)
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hand_detector.process(img, draw=False)
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position = hand_detector.find_position(img)
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left_finger = position['Left'].get(8, None)
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if left_finger:
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cv2.circle(img, (left_finger[0], left_finger[1]),10, (0, 0, 255), cv2.FILLED)
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right_finger = position['Right'].get(8, None)
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if right_finger:
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cv2.circle(img, (right_finger[0], right_finger[1]),10, (0, 255, 0), cv2.FILLED)
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cv2.imshow('Video', img)
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k = cv2.waitKey(1)
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if k == ord('q'):
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break
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camera.release()
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cv2.destroyAllWindows()

‎code/8/handUtils.py

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import cv2
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import mediapipe as mp
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class HandDetector():
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def __init__(self):
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self.hand_detector = mp.solutions.hands.Hands()
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self.drawer = mp.solutions.drawing_utils
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def process(self, img, draw=True):
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img_rgb = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
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self.hands_data = self.hand_detector.process(img_rgb)
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if draw:
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if self.hands_data.multi_hand_landmarks:
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for handlms in self.hands_data.multi_hand_landmarks:
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self.drawer.draw_landmarks(img, handlms, mp.solutions.hands.HAND_CONNECTIONS)
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def find_position(self, img):
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h, w, c = img.shape
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position = {'Left': {}, 'Right': {}}
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if self.hands_data.multi_hand_landmarks:
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i = 0
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for point in self.hands_data.multi_handedness:
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score = point.classification[0].score
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if score >= 0.8:
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label = point.classification[0].label
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hand_lms = self.hands_data.multi_hand_landmarks[i].landmark
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for id, lm in enumerate(hand_lms):
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x, y = int(lm.x * w), int(lm.y * h)
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position[label][id] = (x, y)
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i = i + 1
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return position

‎code/8/requirements.txt

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# My Python version is: 3.8.9
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opencv-python==4.5.4.60
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mediapipe==0.8.9

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