How to find contours in a region of interest in image using opencv and Python?
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while(True):
_, frame = cap.read() hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) a, b = 0, 0 height, width, layers = frame.shape start_height = height - height left_x = width - 500 #right_area = frame[y:y+height, x:x+300] #left_area = frame[y:y+height,] black_min = np.array([0, 0, 0], np.uint8) black_max = np.array([179, 255, 70], np.uint8) red_min = np.array([0, 70, 50], np.uint8) red_max = np.array([20, 255, 255], np.uint8) red1 = np.array([170, 70, 50], np.uint8) red2 = np.array([180, 255, 255], np.uint8) red_mask = cv2.inRange(hsv, red1, red2) red_mask2 = cv2.inRange(hsv, red_min, red_max) kernel = np.ones((7, 7), "uint8") red_mask = cv2.dilate(red_mask, kernel) res_red = cv2.bitwise_and(frame, frame, mask=red_mask) red_mask2 = cv2.dilate(red_mask2, kernel) res_red2 = cv2.bitwise_and(frame, frame, mask=red_mask2) area1 = frame[a:a + height, b:b + 300] area2 = frame[a:a + height, left_x:left_x + 500] cnts, _ = cv2.findContours(red_mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) for pic, c in enumerate(cnts): area = cv2.contourArea(c) if (700 > area > 350): x,y,w,h = cv2.boundingRect(c) cv2.rectangle(frame, (x, y),(x + w, y + h),(0, 0, 255), 2) cv2.putText(frame, "Red detected", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 255)) cv2.imshow("Video from camera", frame) if cv2.waitKey(10) & 0xFF == ord('q'): breakI belive that for C++ the solution looks like this:
findContours(Mask(cv::Rect(x,y,width,height)), contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0,0) );
How can I change this line to get the results I want?
this is the area I'm interested in frame[a:a + height, b:left_x + 300] Thanks in advance!
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while(True):
_, frame = cap.read() hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) a, b = 0, 0 height, width, layers = frame.shape start_height = height - height left_x = width - 500 #right_area = frame[y:y+height, x:x+300] #left_area = frame[y:y+height,] black_min = np.array([0, 0, 0], np.uint8) black_max = np.array([179, 255, 70], np.uint8) red_min = np.array([0, 70, 50], np.uint8) red_max = np.array([20, 255, 255], np.uint8) red1 = np.array([170, 70, 50], np.uint8) red2 = np.array([180, 255, 255], np.uint8) red_mask = cv2.inRange(hsv, red1, red2) red_mask2 = cv2.inRange(hsv, red_min, red_max) kernel = np.ones((7, 7), "uint8") red_mask = cv2.dilate(red_mask, kernel) res_red = cv2.bitwise_and(frame, frame, mask=red_mask) red_mask2 = cv2.dilate(red_mask2, kernel) res_red2 = cv2.bitwise_and(frame, frame, mask=red_mask2) area1 = frame[a:a + height, b:b + 300] area2 = frame[a:a + height, left_x:left_x + 500] cnts, _ = cv2.findContours(red_mask, cv2.RETR_TREE, cv2.CHAIN_APPROX_SIMPLE) for pic, c in enumerate(cnts): area = cv2.contourArea(c) if (700 > area > 350): x,y,w,h = cv2.boundingRect(c) cv2.rectangle(frame, (x, y),(x + w, y + h),(0, 0, 255), 2) cv2.putText(frame, "Red detected", (x, y), cv2.FONT_HERSHEY_SIMPLEX, 1.0, (0, 0, 255)) cv2.imshow("Video from camera", frame) if cv2.waitKey(10) & 0xFF == ord('q'): breakI belive that for C++ the solution looks like this:
findContours(Mask(cv::Rect(x,y,width,height)), contours, hierarchy, RETR_TREE, CHAIN_APPROX_SIMPLE, Point(0,0) );
How can I change this line to get the results I want?
this is the area I'm interested in frame[a:a + height, b:left_x + 300] Thanks in advance!
@coutKateM and how is this related to the Qt framework?
Your code snippet has no Qt object at all!
It looks like you may need to ask this question in an OpenCV forum... more chances to get proper answers I guess
