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WebCV \u3067Web\u30ab\u30e1\u30e9\u306e\u6620\u50cf\u304b\u3089\u52d5\u304f\u3082\u306e\u306b\u77e9\u5f62\u3067\u56f2\u3044\u305f\u3044<\/p>\n<\/span><\/span><\/div><\/div><\/div><\/div>\n\n\n\n![\"Gemini\"](\"https:\/\/www.gravatar.com\/avatar\/?d=mm\")
Gemini<\/div><\/div>
\n
![\"\"](\"https:\/\/www.bigriver.jp\/wp-content\/uploads\/2024\/05\/image-80.png\")
<\/figure>\n\n\n\n![\"\"](\"https:\/\/www.bigriver.jp\/wp-content\/uploads\/2024\/05\/image-81-635x1024.png\")
<\/figure>\n\n\n\n![\"\"](\"https:\/\/www.bigriver.jp\/wp-content\/uploads\/2024\/05\/image-82-711x1024.png\")
<\/figure>\n<\/span><\/span><\/div><\/div><\/div><\/div>\n\n\n\n<\/div>\n\n\n\n
\u5b9f\u306f\u79c1\u306e\u6700\u521d\u306e\u4f9d\u983c\u6587\u7ae0\u3067\u201dOpenCV\u201d\u3092\u201dWebCV\u201d\u3068\u30ad\u30fc\u5165\u529b\u3092\u9593\u9055\u3048\u3066\u3044\u307e\u3059\u3002\u3000\u305d\u308c\u306b\u5bfe\u3057\u3066 Gemini \u306f<\/p>\n\n\n\n
\u300cWeb\u30ab\u30e1\u30e9\u306e\u6620\u50cf\u304b\u3089\u52d5\u304f\u3082\u306e\u3092\u691c\u51fa\u3057\u3001\u77e9\u5f62\u3067\u56f2\u3080\u306b\u306f\u3001OpenCV\u306e\u6a5f\u80fd\u3092\u4f7f\u3046\u306e\u304c\u4e00\u822c\u7684\u3067\u3059\u3002WebCV\u3068\u3044\u3046\u30e9\u30a4\u30d6\u30e9\u30ea\u306f\u5b58\u5728\u3057\u306a\u3044\u305f\u3081\u3001OpenCV\u3092\u7528\u3044\u305f\u65b9\u6cd5\u3092\u8aac\u660e\u3057\u307e\u3059\u3002<\/strong>\u300d<\/p>\n\n\n\n\u3068\u3001WebCV\u3067\u306f\u306a\u304f OpenCV\u306e\u8a71\u3068\u3057\u3066\u8aac\u660e\u3057\u307e\u3059\u3068\u3061\u3083\u3093\u3068\u9593\u9055\u3044\u3092\u8a8d\u8b58\u3057\u3001\u672c\u5f53\u306f\u4f55\u3060\u3063\u305f\u306e\u304b\u985e\u63a8\u3057\u56de\u7b54\u3057\u3066\u304f\u308c\u3066\u3044\u307e\u3059\u3002\u3000\u79c1\u3082\u751f\u6210AI\u51fa\u59cb\u3081\u3067\u3042\u307e\u308a\u89e6\u3063\u3066\u3044\u306a\u304b\u3063\u305f\u3053\u308d\u306f\u751f\u6210AI\u306e\u6b63\u3057\u3044\u4f7f\u3044\u65b9\u307f\u305f\u3044\u306a\u60c5\u5831\u3092\u3082\u3068\u306b\u3069\u3093\u306a\u5f79\u5272\u3067\u3001\u3053\u3093\u306a\u72b6\u6cc1\u3067\u56de\u7b54\u306f\u3053\u3046\u3053\u3046\u307b\u3057\u3044\u3068\u8272\u3005\u5de5\u592b\u3057\u306a\u3044\u3068\u3044\u3051\u306a\u3044\u3068\u601d\u3063\u3066\u3044\u307e\u3057\u305f\u3002\u3000\u6700\u8fd1\u672c\u6765\u4f7f\u308f\u306a\u304f\u3066\u3082\u826f\u3044\u5834\u9762\u3067\u3082\u51fa\u6765\u308b\u9650\u308a Gemini \u306b\u805e\u3044\u3066\u3044\u308b\u306e\u3067\u3059\u304c\u304b\u306a\u308a\u96d1\u306b\u554f\u3044\u304b\u3051\u3066\u3082\u3061\u3083\u3093\u3068\u7b54\u3048\u304c\u8fd4\u3063\u3066\u304d\u307e\u3059\u3002\u3000\u611f\u899a\u3068\u3057\u3066\u306f10\u3042\u308b\u3046\u3061\u306e2~3\u306e\u96d1\u306aINPUT\u30677-10\u3001\u5834\u5408\u306b\u3088\u3063\u3066\u306f10\u4ee5\u4e0a\u306e\u56de\u7b54\u304c\u8fd4\u3063\u3066\u304f\u308b\u611f\u3058\u3067\u3059\u3002\u3000\u3082\u3061\u308d\u3093\u56de\u7b54\u5185\u5bb9\u306e\u6b63\u8aa4\u306f\u3042\u308a\u307e\u3059\u304c\u305d\u3093\u306a\u611f\u89e6\u3067\u3059\u3002<\/p>\n\n\n\n
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<\/span>\u30b3\u30fc\u30c9<\/span><\/span><\/span><\/h2>\n\n\n\n\u9014\u4e2d\u8272\u3005\u4fee\u6b63\u3057\u3066\u3044\u307e\u3059\u304c\u6700\u7d42\u7684\u306a\u30b3\u30fc\u30c9\u306f\u4ee5\u4e0b\u3002<\/p>\n\n\n\n
import cv2\nimport numpy as np\n\n# get background image\ncap = cv2.VideoCapture(0)\nret, frame = cap.read()\nif not ret:\n print('Error: cannot capture')\n cap.release()\n cv2.destroyAllWindows()\n exit()\nbg = frame.copy()\n\nwhile True:\n # read a frame from the camera\n ret, frame = cap.read()\n if not ret:\n break\n\n # calculate the difference between the background and the frame\n diff = cv2.absdiff(frame, bg)\n diff_gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)\n\n # threshold\n _, thresh = cv2.threshold(diff_gray, 30, 255, cv2.THRESH_BINARY)\n\n # find contours\n contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n\n # draw contours\n for countour in contours:\n if cv2.contourArea(countour) < 250:\n continue\n x,y,w,h = cv2.boundingRect(countour)\n cv2.rectangle(frame, (x,y), (x+w, y+h), (0, 255, 0), 2)\n\n # show the frame\n cv2.imshow('frame', frame)\n\n # 'q' key is pressed\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break \n\n# release the camera\ncap.release()\ncv2.destroyAllWindows()<\/code><\/pre>\n\n\n\n<\/div>\n\n\n\n
\u5b9f\u884c\u7d50\u679c\u306f\u3053\u3061\u3089\u3002\u3000\u5b9f\u969b\u306b\u306f\u30ea\u30a2\u30eb\u30bf\u30a4\u30e0\u306b\u52d5\u304f\u3082\u306e\uff08\u6620\u50cf\u306f\u4ea4\u5dee\u70b9\u306a\u306e\u3067\u4e3b\u306b\u81ea\u52d5\u8eca\uff09\u306b\u3064\u3044\u3066\u7dd1\u8272\u306e\u67a0\u304c\u8ffd\u968f\u3057\u3066\u3044\u304d\u307e\u3059\u3002\u3000<\/p>\n\n\n\n
\u307e\u305f\u3001\u4eca\u56de\u306f\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u306f\u3044\u308c\u3066\u3044\u306a\u3044\u305f\u3081\u30b9\u30af\u30ea\u30fc\u30f3\u30b7\u30e7\u30c3\u30c8\u3092\u4e00\u5ea6\u53d6\u5f97\u3057\u30e2\u30b6\u30a4\u30af\u3092\u624b\u52d5\u3067\u304b\u3051\u3066\u3044\u307e\u3059\u3002\u3000\u3053\u306e\u5f8c\u3001\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u3092\u8ffd\u52a0\u3057\u305f\u30d7\u30ed\u30b0\u30e9\u30e0\u3082\u7d39\u4ecb\u3057\u307e\u3059\u3002<\/p>\n\n\n\n![\"\"](\"https:\/\/www.bigriver.jp\/wp-content\/uploads\/2024\/05\/image-83.png\")
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<\/span>\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u3092\u8ffd\u52a0<\/span><\/span><\/span><\/h2>\n\n\n\n\u30d7\u30ed\u30b0\u30e9\u30e0\u306e\u4e2d\u3067\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u3092\u8ffd\u52a0\u3057\u305f\u30b3\u30fc\u30c9\u306f\u3053\u3061\u3089\u3002\u3000\u592a\u6587\u5b57\u304c\u8ffd\u52a0\u90e8\u5206\u3067\u3059\u3002<\/p>\n\n\n\n
import cv2\nimport numpy as np\n\ndef mosaic(src, ratio=0.2):\n small = cv2.resize(src, None, fx=ratio, fy=ratio, interpolation=cv2.INTER_NEAREST)\n return cv2.resize(small, src.shape[:2][::-1], interpolation=cv2.INTER_NEAREST)<\/strong>\n\n# get background image\ncap = cv2.VideoCapture(0)\nret, frame = cap.read()\nif not ret:\n print('Error: cannot capture')\n cap.release()\n cv2.destroyAllWindows()\n exit()\nbg = frame.copy()\n\nwhile True:\n # read a frame from the camera\n ret, frame = cap.read()\n if not ret:\n break\n\n # calculate the difference between the background and the frame\n diff = cv2.absdiff(frame, bg)\n diff_gray = cv2.cvtColor(diff, cv2.COLOR_BGR2GRAY)\n\n # threshold\n _, thresh = cv2.threshold(diff_gray, 30, 255, cv2.THRESH_BINARY)\n\n # find contours\n contours, _ = cv2.findContours(thresh, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)\n\n # draw contours\n for countour in contours:\n if cv2.contourArea(countour) < 200:\n continue\n x,y,w,h = cv2.boundingRect(countour)\n cv2.rectangle(frame, (x,y), (x+w, y+h), (0, 255, 0), 2)\n\n # mosaic the frame\n frame = mosaic(frame)<\/strong>\n\n # show the frame\n cv2.imshow('frame', frame)\n\n # 'q' key is pressed\n if cv2.waitKey(1) & 0xFF == ord('q'):\n break \n\n# release the camera\ncap.release()\ncv2.destroyAllWindows()<\/code><\/pre>\n\n\n\n<\/div>\n\n\n\n
\u5b9f\u884c\u7d50\u679c\u306f\u3053\u3061\u3089\u3002\u3000Windows\u306e\u6a5f\u80fd\u3067MPEG\u306b\u3057\u305f\u3082\u306e\u3092\u5225\u9014GIF\u306b\u3057\u3066\u3044\u307e\u3059\u3002\u3000\u30b5\u30a4\u30ba\u3092\u5c0f\u3055\u304f\u3059\u308b\u305f\u3081\u306b\u4f4e\u753b\u8cea\u306b\u3057\u3066\u3044\u308b\u305f\u3081\u3061\u3087\u3063\u3068\u898b\u3065\u3089\u3044\u3067\u3059\u304c\u5404\u30d5\u30ec\u30fc\u30e0\u304c\u30e2\u30b6\u30a4\u30af\u51e6\u7406\u3055\u308c\u3066\u3044\u308b\u3053\u3068\u304c\u308f\u304b\u308b\u3068\u601d\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
<\/span><\/p>\n\n\n\n![\"\"](\"https:\/\/www.bigriver.jp\/wp-content\/uploads\/2024\/05\/frame-2024-05-20-18-27-05-1.gif\")
<\/figure>\n\n\n\n<\/div>\n\n\n\n
functions have different types, the output array type must be explicitly specified in function \u2018cv::arithm_op\u2019<\/span><\/span><\/h2>\n\n\n\nGemini\u304b\u3089\u306e\u30b3\u30fc\u30c9\u3092\u5b9f\u884c\u6642\u3001\u4e0b\u8a18\u306e\u30a8\u30e9\u30fc\u304c\u767a\u751f\u3057\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
Traceback (most recent call last):\n File \"c:\\Users\\XXXXXXX\\OneDrive - bigriver\\\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\\VSC_python\\opencv6.py\", line 21, in <module>\n diff = cv2.absdiff(frame, bg)\n ^^^^^^^^^^^^^^^^^^^^^^\ncv2.error: OpenCV(4.9.0) D:\\a\\opencv-python\\opencv-python\\opencv\\modules\\core\\src\\arithm.cpp:674: error: (-5:Bad argument) When the input arrays in add\/subtract\/multiply\/divide functions have different types, the output array type must be explicitly specified in function 'cv::arithm_op'<\/code><\/pre>\n\n\n\n<\/div>\n\n\n\n
\u201dthe output array type must be explicitly specified in function \u2018cv::arithm_op\u2019\u201d\u304c\u30dd\u30a4\u30f3\u30c8\u3068\u306a\u308a\u305d\u3046\u3067\u3059\u3002\u3000\u5f93\u6765\u3067\u3059\u3068 OpenCV \u306e\u30c9\u30ad\u30e5\u30e1\u30f3\u30c8\u3092\u78ba\u8a8d\u3057\u305f\u308a arithm_op \u306e\u30bd\u30fc\u30b9\u30b3\u30fc\u30c9\u3092\u78ba\u8a8d\u3057\u305f\u308a\u3001\u30e1\u30c3\u30bb\u30fc\u30b8\u901a\u308a array type \u3092\u660e\u793a\u7684\u306b(explicitly)\u306b\u6307\u5b9a\u3055\u308c\u3066\u3044\u308b\u304b\u78ba\u8a8d\u3059\u308b\u3053\u3068\u306b\u306a\u308a\u307e\u3059\u3002<\/p>\n\n\n\n
\u4eca\u56de\u306f Gemini \u306b\u805e\u3044\u3066\u307f\u307e\u3059\u3002\u3000\u4e0a\u8a18\u306e\u30a8\u30e9\u30fc\u30b3\u30fc\u30c9\u3092\u5f35\u308a\u4ed8\u3051\u308b\u3060\u3051\u3067\u7b54\u3048\u306f\u8fd4\u3063\u3066\u304d\u307e\u3059\u3002<\/p>\n\n\n\n
Gemini<\/div><\/div>
\n
\u3053\u306e\u30a8\u30e9\u30fc\u306f\u3001cv2.absdiff<\/code> \u95a2\u6570\u3067\u6bd4\u8f03\u3059\u308b2\u3064\u306e\u753b\u50cf (frame<\/code> \u3068 bg<\/code>) \u306e\u30c7\u30fc\u30bf\u578b\u304c\u7570\u306a\u3063\u3066\u3044\u308b\u305f\u3081\u306b\u767a\u751f\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n\u5177\u4f53\u7684\u306b\u306f\u3001<\/p>\n\n\n\n
\nframe<\/code>: Web\u30ab\u30e1\u30e9\u304b\u3089\u8aad\u307f\u8fbc\u307e\u308c\u305f\u753b\u50cf\u3067\u3001\u901a\u5e38\u306f uint8<\/code> (\u7b26\u53f7\u306a\u30578\u30d3\u30c3\u30c8\u6574\u6570) \u578b\u3067\u3059\u3002<\/li>\n\n\n\nbg<\/code>: \u6700\u521d\u306e\u30d5\u30ec\u30fc\u30e0\u3092\u30b3\u30d4\u30fc\u3057\u305f\u3082\u306e\u3067\u3001float32<\/code> (\u5358\u7cbe\u5ea6\u6d6e\u52d5\u5c0f\u6570\u70b9\u6570) \u578b\u306b\u306a\u3063\u3066\u3044\u307e\u3059\u3002<\/li>\n<\/ul>\n\n\n\nOpenCV\u306e\u7b97\u8853\u6f14\u7b97\u95a2\u6570 (cv2.absdiff<\/code>, cv2.add<\/code>, cv2.subtract<\/code> \u306a\u3069) \u3067\u306f\u3001\u5165\u529b\u753b\u50cf\u306e\u30c7\u30fc\u30bf\u578b\u304c\u7570\u306a\u308b\u5834\u5408\u3001\u51fa\u529b\u753b\u50cf\u306e\u30c7\u30fc\u30bf\u578b\u3092\u660e\u793a\u7684\u306b\u6307\u5b9a\u3059\u308b\u5fc5\u8981\u304c\u3042\u308a\u307e\u3059\u3002<\/p>\n\n\n\n<\/p>\n\n\n\n
\u89e3\u6c7a\u65b9\u6cd5<\/strong><\/p>\n\n\n\nbg<\/code> \u306e\u30c7\u30fc\u30bf\u578b\u3092 uint8<\/code> \u306b\u5909\u63db\u3059\u308b\u304b\u3001cv2.absdiff<\/code> \u306e\u51fa\u529b\u30c7\u30fc\u30bf\u578b\u3092\u660e\u793a\u7684\u306b\u6307\u5b9a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n<\/p>\n\n\n\n
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\u89e3\u6c7a\u65b9\u6cd5<\/strong><\/p>\n\n\n\nbg<\/code> \u306e\u30c7\u30fc\u30bf\u578b\u3092 uint8<\/code> \u306b\u5909\u63db\u3059\u308b\u304b\u3001cv2.absdiff<\/code> \u306e\u51fa\u529b\u30c7\u30fc\u30bf\u578b\u3092\u660e\u793a\u7684\u306b\u6307\u5b9a\u3057\u307e\u3059\u3002<\/p>\n\n\n\n<\/p>\n\n\n\n
\uff08\u7701\u7565\uff09<\/p>\n\n\n\n
<\/p>\n<\/span><\/span><\/div><\/div><\/div><\/div>\n\n\n\n<\/div>\n\n\n\n
\u4eca\u56de\u306f\u7701\u7565\u3057\u307e\u3057\u305f\u304c\u4fee\u6b63\u6e08\u306e\u30b3\u30fc\u30c9\u5168\u4f53\u3082\u63d0\u793a\u3057\u3066\u304f\u308c\u307e\u3059\u3002\u3000\u3042\u3089\u3086\u308b\u72b6\u6cc1\u306b\u5bfe\u5fdc\u51fa\u6765\u308b\u308f\u3051\u3067\u306f\u306a\u3044\u3068\u601d\u3044\u307e\u3059\u304c\u521d\u5fc3\u8005\u306e\u30d7\u30ed\u30b0\u30e9\u30df\u30f3\u30b0\u306e\u5148\u751f\u3068\u3057\u3066 Gemini \u306f\u5fc5\u8981\u5341\u5206\u4ee5\u4e0a\u306e\u529b\u3092\u3082\u3063\u3066\u3044\u308b\u306e\u304b\u306a\u3068\u611f\u3058\u307e\u3057\u305f\u3002<\/p>\n\n\n\n
\u6700\u7d42\u7684\u306b\u306f\u4ee5\u4e0b\u306e\u90e8\u5206\u3092\u4fee\u6b63\u3057\u30a8\u30e9\u30fc\u304c\u89e3\u6d88\u3057\u3066\u3044\u307e\u3059\u3002 \u201c.astype(np.float32)\u201d \u3092\u524a\u9664\u3057\u3066\u3044\u307e\u3059\u3002<\/p>\n\n\n\n
#\u4fee\u6b63\u524d\nbg = frame.copy().astype(np.float32)\n\n\n#\u4fee\u6b63\u5f8c\nbg = frame.copy() # \u2190\u4fee\u6b63\u7b87\u6240<\/code><\/pre>\n\n\n\n<\/p>\n\n\n\n
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\u4ee5\u4e0a<\/p>\n\n\n\n
<\/p>\n","protected":false},"excerpt":{"rendered":"
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