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Threshold changed to: \"+str(thr))\n+\n+\n+def removeBG(videostream):\n+    fgmask = bgModel.apply(videostream)\n+    kernel = np.ones((3, 3), np.uint8)\n+    fgmask = cv2.erode(fgmask, kernel, iterations=1)\n+    result = cv2.bitwise_and(videostream, videostream, mask=fgmask)\n+    return result\n+\n+\n+def findFingers(result,drawing):  # -> finished bool, count: finger count\n+    #  convexity defect\n+    hull = cv2.convexHull(result, returnPoints=False)\n+    if len(hull) > 3:\n+        defects = cv2.convexityDefects(result, hull)\n+        if type(defects) != type(None):\n+            count = 0\n+            for i in range(defects.shape[0]):  # calculate the angle\n+                s, e, f, d = defects[i][0]\n+                start = tuple(result[s][0])\n+                end = tuple(result[e][0])\n+                far = tuple(result[f][0])\n+                a = math.sqrt((end[0] - start[0]) ** 2 + (end[1] - start[1]) ** 2)\n+                b = math.sqrt((far[0] - start[0]) ** 2 + (far[1] - start[1]) ** 2)\n+                c = math.sqrt((end[0] - far[0]) ** 2 + (end[1] - far[1]) ** 2)\n+                angle = math.acos((b ** 2 + c ** 2 - a ** 2) / (2 * b * c))  # cosine theorem\n+                if angle <= math.pi / 2:  # angle less than 90 degree, treat as fingers\n+                    count += 1\n+                    cv2.circle(drawing, far, 8, [211, 84, 0], -1)\n+            return True, count\n+    return False, 0\n+\n+# Do camera operations\n+camera_input = int(input('Enter camera number: '))\n+camera = cv2.VideoCapture(camera_input)\n+camera.set(10,200)\n+font = cv2.FONT_HERSHEY_SIMPLEX\n+cv2.namedWindow('trackbar')\n+cv2.createTrackbar('trh1', 'trackbar', threshold, 100, printThreshold)\n+print(\"Press b to capture background & begin detection or r to reset\")\n+\n+\n+while camera.isOpened():\n+    ret, videostream = camera.read()\n+    threshold = cv2.getTrackbarPos('trh1', 'trackbar')\n+    videostream = cv2.bilateralFilter(videostream, 5, 50, 100)  # smoothing filter\n+    videostream = cv2.flip(videostream, 1)  # flip the videostream horizontally\n+    cv2.rectangle(videostream, (int(capture_region_x * videostream.shape[1]), 0),\n+                 (videostream.shape[1], int(capture_region_y * videostream.shape[0])), (255, 0, 0), 2)\n+    cv2.imshow('original', videostream)\n+\n+    #  Main operation\n+    if isBgCaptured == 1:  # Only runs once background is captured\n+        img = removeBG(videostream)\n+        img = img[0:int(capture_region_y * videostream.shape[0]),\n+                    int(capture_region_x * videostream.shape[1]):videostream.shape[1]]  # clip the ROI\n+        #cv2.imshow('mask', img) #show mask image\n+\n+        # convert the image into binary image\n+        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)\n+        blur = cv2.GaussianBlur(gray, (blurValue, blurValue), 0)\n+        #cv2.imshow('blurred', blur) # show blur image\n+        ret, thresh = cv2.threshold(blur, threshold, 255, cv2.THRESH_BINARY)","path":"recognition.py","position":81,"original_position":81,"commit_id":"8e99a77508932c23f5e3f19b6c833dd18ea6707f","original_commit_id":"8e99a77508932c23f5e3f19b6c833dd18ea6707f","user":{"login":"isaacvandor","id":9000810,"avatar_url":"https://avatars0.githubusercontent.com/u/9000810?v=4","gravatar_id":"","url":"https://api.github.com/users/isaacvandor","html_url":"https://github.com/isaacvandor","followers_url":"https://api.github.com/users/isaacvandor/followers","following_url":"https://api.github.com/users/isaacvandor/following{/other_user}","gists_url":"https://api.github.com/users/isaacvandor/gists{/gist_id}","starred_url":"https://api.github.com/users/isaacvandor/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/isaacvandor/subscriptions","organizations_url":"https://api.github.com/users/isaacvandor/orgs","repos_url":"https://api.github.com/users/isaacvandor/repos","events_url":"https://api.github.com/users/isaacvandor/events{/privacy}","received_events_url":"https://api.github.com/users/isaacvandor/received_events","type":"User","site_admin":false},"body":"Yeah 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