-215
opencv
type_error
ai_generated
true
cv::error: (-215:Assertion failed) _src.type() == CV_8UC1 in function 'cv::findContours'
ID: opencv/contours-not-found-in-binary-image
90%Fix Rate
85%Confidence
1Evidence
2024-03-15First Seen
Version Compatibility
| Version | Status | Introduced | Deprecated | Notes |
|---|---|---|---|---|
| 4.5.5 | active | — | — | — |
| 4.8.0 | active | — | — | — |
| 4.9.0 | active | — | — | — |
Root Cause
findContours requires an 8-bit single-channel binary image, but the input is multi-channel or non-8-bit.
generic中文
findContours 需要8位单通道二值图像,但输入图像是多通道或非8位类型。
Official Documentation
https://docs.opencv.org/4.x/d3/dc0/group__imgproc__shape.html#gadf1ad6a0b82947fa1fe3c3d497f260e0Workarounds
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95% success img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) _, img_bin = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY) contours, _ = cv2.findContours(img_bin, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) _, img_bin = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY) contours, _ = cv2.findContours(img_bin, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
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85% success edges = cv2.Canny(img_gray, 50, 150) contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
edges = cv2.Canny(img_gray, 50, 150) contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
中文步骤
img_gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) _, img_bin = cv2.threshold(img_gray, 127, 255, cv2.THRESH_BINARY) contours, _ = cv2.findContours(img_bin, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
edges = cv2.Canny(img_gray, 50, 150) contours, _ = cv2.findContours(edges, cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_SIMPLE)
Dead Ends
Common approaches that don't work:
-
60% fail
Grayscale may still have multiple channels (e.g., 3-channel grayscale) or be 16-bit. findContours explicitly needs CV_8UC1.
-
40% fail
Canny output is binary but may still have non-zero values outside 0-255 if not properly normalized; thresholding ensures binary.
-
70% fail
Resize does not change channel count; the image remains 3-channel.