Today, we have a video to achieve real-time detection of small color of the object instance, has three primary color video objects, we only detect red and green spherical object, as shown below:
The first step required to open the video (or camera):
cap = cv2.VideoCapture ( '1.mp4') # open a video file # cap = cv2.VideoCapture (0) # open USB camera
Cycles then need to take the frames, color object detection. Detecting HSV color of an object using a color filter threshold value, the threshold value is set to the key HSV, HSV color following table are commonly used:
But the picture also need specific tools to write your own take to extract a small HSV value of the target on the picture, and then manually set threshold, such as in the picture above the red and green we use HSV thresholds are as follows:
lower_green = np.array ([35, 110 , 106]) # green range low threshold upper_green = np.array ([77, 255 , 255]) # green range of the high threshold lower_red = np.array ([0, 127 , 128 ]) # red range low threshold upper_red = np.array ([10, 255 , 255]) # high threshold red range
The next step is a filtering process, the outline extraction and the final result is indicative denoted with a rectangular box object detection, while the color marked with putText function, the complete code and final results are as follows:
complete code:
# - * - Coding: cp936 - * -
Import numpy AS NP
Import CV2
font = cv2.FONT_HERSHEY_SIMPLEX
lower_green np.array = ([35, 110, 106]) # green range low threshold
upper_green = np.array ([77, 255 , 255]) # green range of the high threshold
lower_red = np.array ([0, 127 , 128]) # red range low threshold
upper_red = np.array ([10, 255 , 255]) # high threshold red range
cap = cv2 .VideoCapture ( '1.mp4') # open a video file
# cap = cv2.VideoCapture (0) # open USB camera
if (cap.isOpened ()): # video open succeeded
In Flag. 1 =
the else:
In Flag = 0
NUM = 0
IF (In Flag):
the while (True):
RET, frame = cap.read () reads a #
# IF (frame None IS):
IF RET == False: reading frames failed #
break
= cv2.cvtColor hsv_img (Frame, cv2.COLOR_BGR2HSV)
mask_green = cv2.inRange (hsv_img, lower_green, upper_green) # puncturing range according to the color selected from
mask_red = cv2.inRange (hsv_img, lower_red, upper_red) # puncturing range according to the color selected from
mask_green = cv2.medianBlur (mask_green, 7) # median filter
mask_red = cv2.medianBlur (mask_red, 7) # median filter
mask = cv2.bitwise_or (mask_green, mask_red)
cv2.imshow ( 'mask_green', mask_green)
cv2.imshow ( 'mask_red', mask_red)
cv2.imshow ( 'mask', mask)
mask_green, Contours, cv2.findContours = Hierarchy (mask_green, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
mask_red, contours2, hierarchy2 = cv2.findContours(mask_red, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE)
for CNT in Contours:
(X, Y, W, H) = cv2.boundingRect (cnt)
cv2.rectangle(frame, (x, y), (x + w, y + h), (0, 255, 255), 2)
cv2.putText(frame, "green", (x, y - 5), font, 0.7, (0, 255, 0), 2)
for cnt2 in contours2:
(x2, y2, w2, h2) = cv2.boundingRect(cnt2)
cv2.rectangle(frame, (x2, y2), (x2 + w2, y2 + h2), (0, 255, 255), 2)
cv2.putText(frame, "red", (x2, y2 - 5), font, 0.7, (0, 0, 255), 2)
num = num + 1
cv2.imshow("result", frame)
cv2.imwrite("imgs/%d.jpg"%num, frame)
if cv2.waitKey(20) & 0xFF == 27:# Press Esc to exit
break
cv2.waitKey(0)
cv2.destroyAllWindows()
The net effect animation:
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