predict.py 文件源码

def to_binary_mask(mask, t=0.00001):
    mask = inverse_preprocessing(mask)

    ### Threshold the RGB image  - This step increase sensitivity
    mask[mask > t] = 255
    mask[mask <= t] = 0

    ### To grayscale and normalize
    mask_gray = cv2.cvtColor(mask, cv2.COLOR_BGR2GRAY)
    mask_gray = cv2.normalize(src=mask_gray, dst=None, alpha=0, beta=255, norm_type=cv2.NORM_MINMAX, dtype=cv2.CV_8UC1)

    ### Auto binary threshold
    (thresh, mask_binary) = cv2.threshold(mask_gray, 128, 255, cv2.THRESH_BINARY | cv2.THRESH_OTSU)
    return mask_binary