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import cv2
import numpy as np
def pitch(img):
"""
Detects the cricket pitch in a given image frame using color-based segmentation and edge detection.
Args:
img: The input image frame (BGR format).
Returns:
contours: A list of contours detected in the color-masked and edge-processed image,
presumed to be the pitch. Returns an empty list if no contours are found.
"""
imgGray = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
imgBlur= cv2.GaussianBlur(imgGray, (5, 5), 1)
imgThreshold = cv2.Canny(imgBlur, 190, 167)
kernel = np.ones((5, 5))
imgDial = cv2.dilate(imgThreshold, kernel, iterations = 2)
imgThreshold = cv2.erode(imgDial, kernel, iterations = 2)
lower = np.array([190, 167, 99])
upper = np.array([255, 255, 184 ])
mask = cv2.inRange(imgGray, lower, upper)
# Find all contours
width = 264
height = 2256
imgContours = img.copy()
# imgWrap = img.copy()
contours, hierarchy = cv2.findContours(mask, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
return contours
if __name__ == "__main__":
cap = cv2.VideoCapture(r"lbw.mp4") # Adjust path if needed
while True:
frame, img = cap.read()
if not frame:
break
pitch_contours = pitch(img) # Call the placeholder pitch detection
img_contours = img.copy()
for cnt in pitch_contours:
if (
cv2.contourArea(cnt) > 50000
): # Example area filtering - adjust as needed
cv2.drawContours(
img_contours, cnt, -1, (0, 255, 0), 10
) # Draw pitch contours in green
cv2.imshow("Pitch Detection (Placeholder)", img_contours)
if cv2.waitKey(1) & 0xFF == ord("q"):
break
cap.release()
cv2.destroyAllWindows()
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