Why does cv2.polylines crash?

The cv2.polylines function in OpenCV is a powerful tool for drawing multiple line segments, but it can crash due to several reasons. Let's explore common causes and their solutions:

1. Incorrect Data Types:

- The most frequent cause is providing incorrect data types for the pts argument. cv2.polylines expects a NumPy array of integer points. For example, a common mistake is providing a list of floating point values. Ensure your point coordinates are integers. Use np.int32 or similar types:

python
import cv2
import numpy as np

# Incorrect (likely to crash)
# pts = np.array([[10.5, 20.5], [50.1, 60.8], [90.9, 100.2]])

# Correct (using integers)
pts = np.array([[10, 20], [50, 60], [90, 100]], np.int32)
pts = pts.reshape((-1, 1, 2))

img = np.zeros((200, 200, 3), dtype=np.uint8)
cv2.polylines(img, [pts], True, (0, 255, 0), 3)


2. Incorrect Array Shape:

- The shape of the points array needs to be specific. For multiple polylines the input should have a shape like (number_of_polylines, number_of_points_per_polyline, 1, 2) or (number_of_points, 1, 2) for a single polyline. If the points are not in the correct shape, especially if you are not reshaping them properly, a crash can occur. Using reshape((-1, 1, 2)) ensures that the dimensions are appropriate.

python
# Reshaping the array to the correct shape
pts = np.array([[10, 20], [50, 60], [90, 100]], np.int32)
pts = pts.reshape((-1, 1, 2))


3. Incorrect Image Type or Size:

- If your image (the first argument) is not a valid NumPy array or is of an incorrect type or size, cv2.polylines might fail. Make sure your image is an np.uint8 type, such as the result of np.zeros() or reading from an image file with cv2.imread(), and that it is large enough to encompass the specified points.

4. Invalid or Out-of-Bounds Coordinates:

- If your specified points are outside the bounds of the image, OpenCV might throw an error. Ensure that no coordinates exceed the dimensions of your image. Debugging with print statements can help verify this.

python
img = np.zeros((200, 200, 3), dtype=np.uint8)
# Example where coordinates might be too large if the image dimensions are smaller
pts = np.array([[1000, 1000], [1500, 1500]], np.int32).reshape((-1, 1, 2)) # This would cause issues for a smaller image


5. OpenCV Version Issues:

- Occasionally, bugs in specific versions of OpenCV may cause unexpected crashes. It's worthwhile to check if an update is available, or try an older, more stable release if problems persist. You can check your OpenCV version with print(cv2.__version__)

6. Memory Issues:

- If you are dealing with extremely large images or a large number of points, you might be experiencing a memory issue that leads to a crash. Ensure you have sufficient memory and consider optimizing your code or processing smaller portions at a time.

Debugging Steps:

- Double check the data type of the points using print(pts.dtype).

- Print the shape of points using print(pts.shape) and adjust dimensions accordingly.

- Verify image dimensions and types. Use print(img.shape) and print(img.dtype) to inspect the array.

- Ensure points are within image boundaries.

By addressing these potential causes and diligently debugging your code, you should be able to avoid crashes when using cv2.polylines.

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