opencv_visualization

准备一个与原图像相同大小的图像用于debug §

• 参考创建图像

在图像上以特定颜色叠加Mask §

• 单个mask

def mask_overlay(img, mask, color, expand=-1):
    if expand > 0:
        kernel = np.ones((expand, expand), np.uint8) ## only expand on y direction to remove shadow
        mask_ext = cv2.dilate(mask, kernel, iterations=1)
    else:
        mask_ext = mask
    mask_bool = mask_ext > 0
    img[mask_bool] = color

• 多个mask（以list形式）

def show_masks(img, masks, borders=True):
    ## input a list of masks, and show the masks in different color, overlays on the original image
    if len(masks) == 0:
        return
 
    mask_vis = np.ones((masks.shape[1], masks.shape[2], 3), dtype=np.uint8)
    for i in range(masks.shape[0]):
        mask = masks[i].astype(bool)
        color_mask = np.random.randint(0, 256, size=3, dtype=np.uint8)
        mask_vis[mask] = color_mask
        if borders:
            contours, _ = cv2.findContours(mask.astype(np.uint8),cv2.RETR_EXTERNAL, cv2.CHAIN_APPROX_NONE) 
            # Try to smooth contours
            contours = [cv2.approxPolyDP(contour, epsilon=0.01, closed=True) for contour in contours]
            # print(contours)
            # cv2.drawContours(mask_vis, contours, -1, (0,0,1,0.4), thickness=1) 
            cv2.drawContours(mask_vis, contours, -1, (255,0,0), thickness=2) 
    
    alpha=0.4
    overlay = cv2.addWeighted(img, 1 - alpha, mask_vis.astype('uint8'), alpha, 0)
    return overlay