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我正在尝试填充通过分别对 3 个颜色 channel 进行阈值处理而获得的轮廓。
image_original = cv2.imread(original_image_path)
image_contours = np.zeros((image_original.shape[0], image_original.shape[1], 1), dtype=np.uint8)
image_contour = np.zeros((image_original.shape[0], image_original.shape[1], 1), dtype=np.uint8)
image_binary = np.zeros((image_original.shape[0], image_original.shape[1], 1), dtype=np.uint8)
image_area = image_original.shape[0] * image_original.shape[1]
for channel in range(image_original.shape[2]):
ret, image_thresh = cv2.threshold(image_original[:, :, channel], 120, 255, cv2.THRESH_OTSU)
_, contours, hierarchy = cv2.findContours(image_thresh, 1, 1)
for index, contour in enumerate(contours):
if( cv2.contourArea( contour ) > image_area * background_remove_offset ):
del contours[index]
cv2.drawContours(image_contours, contours, -1, (255,255,255), 3)
_, contours, hierarchy = cv2.findContours(image_contours, cv2.RETR_TREE, cv2.CHAIN_APPROX_NONE)
cv2.drawContours(image_contour, max(contours, key = cv2.contourArea), -1, (255, 255, 255), 1)
cv2.imwrite(output_contour_image_path, image_contour)
cv2.drawContours(image_binary, max(contours, key = cv2.contourArea), -1, (255, 255, 255), thickness=-1)
cv2.imwrite(output_binary_image_path, image_binary)
cv2.imshow("binary", image_binary)
这应该通过设置 thickness=-1 来工作，但它只绘制与 thickness=1 相同的 1 厚度的轮廓，特别是在以下行中。
cv2.drawContours(image_binary, max(contours, key = cv2.contourArea), -1, (255, 255, 255), thickness=-1)
结果如下，
除了轮廓厚度为 1 的二值填充图像之外，它应该提出一个二进制填充图像
