姿态估计md文件

data/1.OpenCV初阶/7.OpenCV中的深度学习/4.姿态估计/attitude_estimation.md

+# 使用Python+OpenCV实现姿态估计
+
+
+
+姿态估计使用Opencv+Mediapipe来时实现
+
+**什么是Mediapipe？**
+
+Mediapipe是主要用于构建多模式音频，视频或任何时间序列数据的框架。借助MediaPipe框架，可以构建令人印象深刻的ML管道，例如TensorFlow，TFLite等推理模型以及媒体处理功能。
+
+安装命令：
+
+```
+pip install mediapipe
+```
+
+如果没有安装需要安装，请执行这个命令。
+
+通过视频或实时馈送进行人体姿态估计在诸如全身手势控制，量化体育锻炼和手语识别等各个领域中发挥着至关重要的作用。
+
+例如，它可用作健身，瑜伽和舞蹈应用程序的基本模型。它在增强现实中找到了自己的主要作用。
+
+Media Pipe Pose是用于高保真人体姿势跟踪的框架，该框架从RGB视频帧获取输入并推断出整个人类的33个3D界标。当前最先进的方法主要依靠强大的桌面环境进行推理，而此方法优于其他方法，并且可以实时获得很好的结果。
+
+模型可以预测33个关键点，如下图：
+
+![img](https://gitee.com/wanghao1090220084/cloud-image/raw/master/pose_tracking_full_body_landmarks.png)
+
+我们使用OpenCV+mediapipe实现姿态估计，我已经实现了代码，请大家找出能够正确执行的代码！
+
+# 框架代码
+
+```
+import cv2
+import mediapipe as mp
+import time
+
+mpPose = mp.solutions.pose
+pose = mpPose.Pose()
+mpDraw = mp.solutions.drawing_utils
+cap = cv2.VideoCapture('1.mp4')
+pTime = 0
+#输出检测结果
+
+# do a bit of cleanup
+cv2.destroyAllWindows()
+cap.release()
+
+
+```
+
+# 答案：
+
+```
+while True:
+    success, img = cap.read()
+    if success is False:
+        break
+    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    results = pose.process(imgRGB)
+    if results is None:
+        continue
+    print(results.pose_landmarks)
+    if results.pose_landmarks:
+        mpDraw.draw_landmarks(img, results.pose_landmarks, mpPose.POSE_CONNECTIONS)
+    for id, lm in enumerate(results.pose_landmarks.landmark):
+        h, w, c = img.shape
+    print(id, lm)
+    cx, cy = int(lm.x * w), int(lm.y * h)
+    cv2.circle(img, (cx, cy), 5, (255, 0, 0), cv2.FILLED)
+    cTime = time.time()
+    fps = 1 / (cTime - pTime)
+    pTime = cTime
+    cv2.putText(img, str(int(fps)), (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 3)
+    cv2.imshow("Image", img)
+    key = cv2.waitKey(1) & 0xFF
+```
+
+# 选项
+
+## 读取帧失败后没有终止逻辑
+
+```
+while True:
+    success, img = cap.read()
+    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    results = pose.process(imgRGB)
+    if results is None:
+        continue
+    print(results.pose_landmarks)
+    if results.pose_landmarks:
+        mpDraw.draw_landmarks(img, results.pose_landmarks, mpPose.POSE_CONNECTIONS)
+    for id, lm in enumerate(results.pose_landmarks.landmark):
+        h, w, c = img.shape
+    print(id, lm)
+    cx, cy = int(lm.x * w), int(lm.y * h)
+    cv2.circle(img, (cx, cy), 5, (255, 0, 0), cv2.FILLED)
+    cTime = time.time()
+    fps = 1 / (cTime - pTime)
+    pTime = cTime
+    cv2.putText(img, str(int(fps)), (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 3)
+    cv2.imshow("Image", img)
+    key = cv2.waitKey(1) & 0xFF
+```
+
+## results为None时没有判断
+
+```
+while True:
+    success, img = cap.read()
+    if success is False:
+        break
+    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    results = pose.process(imgRGB)
+    print(results.pose_landmarks)
+    if results.pose_landmarks:
+        mpDraw.draw_landmarks(img, results.pose_landmarks, mpPose.POSE_CONNECTIONS)
+    for id, lm in enumerate(results.pose_landmarks.landmark):
+        h, w, c = img.shape
+    print(id, lm)
+    cx, cy = int(lm.x * w), int(lm.y * h)
+    cv2.circle(img, (cx, cy), 5, (255, 0, 0), cv2.FILLED)
+    cTime = time.time()
+    fps = 1 / (cTime - pTime)
+    pTime = cTime
+    cv2.putText(img, str(int(fps)), (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 3)
+    cv2.imshow("Image", img)
+    key = cv2.waitKey(1) & 0xFF
+```
+
+img的shape顺序不对
+
+```
+while True:
+    success, img = cap.read()
+    if success is False:
+        break
+    imgRGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
+    results = pose.process(imgRGB)
+    if results is None:
+        continue
+    print(results.pose_landmarks)
+    if results.pose_landmarks:
+        mpDraw.draw_landmarks(img, results.pose_landmarks, mpPose.POSE_CONNECTIONS)
+    for id, lm in enumerate(results.pose_landmarks.landmark):
+        c,h, w = img.shape
+    print(id, lm)
+    cx, cy = int(lm.x * w), int(lm.y * h)
+    cv2.circle(img, (cx, cy), 5, (255, 0, 0), cv2.FILLED)
+    cTime = time.time()
+    fps = 1 / (cTime - pTime)
+    pTime = cTime
+    cv2.putText(img, str(int(fps)), (50, 50), cv2.FONT_HERSHEY_SIMPLEX, 1, (255, 0, 0), 3)
+    cv2.imshow("Image", img)
+    key = cv2.waitKey(1) & 0xFF
+```
+