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子豪兄的动作识别
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@Chunsheng13
Chunsheng13 committed May 7, 2022
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474 changes: 474 additions & 0 deletions A单张图像检测.ipynb

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215 changes: 215 additions & 0 deletions B摄像头实时检测.ipynb
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"# opencv-python\n",
"import cv2\n",
"# mediapipe人工智能工具包\n",
"import mediapipe as mp\n",
"#进度条库\n",
"from tqdm import tqdm\n",
"#时间库\n",
"import time"
]
},
{
"cell_type": "code",
"execution_count": 2,
"id": "f288fced-18b7-4657-9465-edbc46b29f62",
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"#导入solution\n",
"mp_pose = mp.solutions.pose\n",
"# #导入绘图函数\n",
"mp_drawing = mp.solutions.drawing_utils\n",
"\n",
"#导入模型\n",
"pose = mp_pose.Pose (static_image_mode=True,\n",
" #是静态图片还是连续视频帧\n",
" model_complexity=1,\n",
" #选择人体姿态关键点检测模型，0性能差但快，2性能好但慢，1介于两者之间\n",
" smooth_landmarks=True,\n",
" #是否平滑关键点\n",
" enable_segmentation=True,\n",
" #是否人体抠图\n",
" min_detection_confidence=0.5, #置信度阈值\n",
" min_tracking_confidence=0.5) # 追踪阈值"
]
},
{
"cell_type": "markdown",
"id": "349dbc2a-1859-48d3-9c4e-472704790ca7",
"metadata": {},
"source": [
"### 处理单帧的函数"
]
},
{
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"execution_count": 3,
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"source": [
"#处理帧函数\n",
"def process_frame(img):\n",
" # BGR转RGB\n",
" img_RGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
" #将RGB图像输入模型，获取预测结果\n",
" results = pose.process(img_RGB)\n",
" #可视化\n",
" mp_drawing. draw_landmarks (img, results.pose_landmarks, mp_pose.POSE_CONNECTIONS)\n",
" # look img(img)\n",
" #在三维真实物理坐标系中可视化以米为单位的检测结果\n",
" # mp_ _drawing. plot_ landmarks (results. pose_ _wor1d_ landmarks, mp_ pose. POSE CONNECTIONS)\n",
" #\n",
" # BGR转RGB\n",
" #\n",
" #img_RGB = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)\n",
" #\n",
" #将RGB图像输入模型，获取预测结果\n",
" #\n",
" #results = hands.process(img_RGB)\n",
" #\n",
" #if results.multi_ hand landmarks: #如果有检测到手\n",
" #遍历每一只检测出的手\n",
" #\n",
" #for hand_ idx in range(len(results . multi_ hand landmarks)):\n",
" #\n",
" #hand _21 = results. multi hand_ landmarks[hand idx] #获取该手的所有关键点坐标\n",
" #\n",
" #mpDraw. draw landmarks (img, hand_ 21, mp hands . HAND_ CONNECTIONS) #可视化\n",
" return img"
]
},
{
"cell_type": "markdown",
"id": "4e5b7d9d-a1d8-418d-81bb-8dc801e1bfb8",
"metadata": {},
"source": [
"### 调用摄像头获取每帧(模板)"
]
},
{
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"source": [
"#调用摄像头逐帧实时处理模板\n",
"#不需修改任何代码，只需修改process_frame函数即可\n",
"#导入opencv-python\n",
"import cv2\n",
"import time\n",
"#获取摄像头，传入0表示获取系统默认摄像头\n",
"cap = cv2 .VideoCapture(0)\n",
"#打开cap \n",
"cap.open(0)\n",
"#无限循环，直到break被触发\n",
"while cap.isOpened():\n",
" #获取画面\n",
" success, frame = cap.read( )\n",
" if not success:\n",
" print( 'Error' )\n",
" break\n",
" \n",
" ## !!!处理帧函数\n",
" frame = process_frame(frame)\n",
" #展示处理后的三通道图像\n",
" cv2.imshow( \"my_window\",frame )\n",
" if cv2.waitKey(1) in [ord('q'),27]: #按键盘上的q或esc退出(在英文输入法下)\n",
" break\n",
"#关闭摄像头\n",
"cap.release()\n",
"#关闭图像窗口\n",
"cv2.destroyAllWindows()"
]
},
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