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OpenCV: Trouble with Color Space Conversion in Video Processing - Unexpected Results Using cvtColor

👀 Views: 43 💬 Answers: 1 📅 Created: 2025-06-13
opencv color-detection video-processing Python

I'm writing unit tests and I need some guidance on I need some guidance on I'm currently working on a video processing application using OpenCV 4.5.3, in which I need to convert frames from BGR to HSV color space to detect certain colors for object tracking. However, I'm working with unexpected results after the conversion. The colors appear to be distorted, and the mask I generate for tracking is not highlighting the expected areas of the frame. Here’s a snippet of the code I’m using to perform the conversion and thresholding: ```python import cv2 import numpy as np # Load video cap = cv2.VideoCapture('input_video.mp4') while cap.isOpened(): ret, frame = cap.read() if not ret: break # Convert BGR to HSV hsv_frame = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV) # Define the color range for masking lower_color = np.array([50, 100, 100]) # Lower bound for green upper_color = np.array([70, 255, 255]) # Upper bound for green # Create mask mask = cv2.inRange(hsv_frame, lower_color, upper_color) # Show results cv2.imshow('Original Frame', frame) cv2.imshow('Mask', mask) if cv2.waitKey(1) & 0xFF == ord('q'): break cap.release() cv2.destroyAllWindows() ``` The color range for the mask is specifically set to detect a green color, but it seems to pick up other colors as well. Additionally, when I visualize the mask, it doesn’t correspond to the green areas in the original frame. I've double-checked the color values, and they seem correct for HSV. I’ve also tried adjusting the lower and upper bounds, but the results remain inconsistent. In some frames, the mask is completely black, and in others, it seems to detect colors that are not even close to the green I aimed to track. I’m not sure if there’s an scenario with the way I’m reading the video frames or how the conversion is being applied. Any insights on what might be going wrong or how to resolve the color detection scenario would be greatly appreciated! I'm working with Python in a Docker container on Windows 10. Hoping someone can shed some light on this. For context: I'm using Python on Linux. Any help would be greatly appreciated!