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# -*- coding: utf-8 -*-
import traceback
import argparse
import os
from moviepy.editor import VideoFileClip
import numpy as np
# rmBlackBorder: remove the black borders of one image
# return: cropped image
def det_image_black_border(
src, # input image
thres, # threshold for cropping: sum([r,g,b] - [0,0,0](black))
shrink, # number of pixels to shrink after the blackBorders removed
):
# remove the black border on both right and left side
nRow = src.shape[0]
nCol = src.shape[1]
left = 0
right = nCol
# for j in range(0, nCol):
# if src[:, j].mean() <= thres:
# left = j + 1
# else:
# break
#
# for j in range(nCol - 1, -1, -1):
# if src[:, j].mean() <= thres:
# right = j
# else:
# break
black_idx = np.where(src.mean(axis=0) <= thres)[0].tolist()
for i in black_idx:
if left < i < nCol // 2:
left = i
elif nCol // 2 < i < right:
right = i
if right - left > 0:
left = left + shrink
right = right - shrink
else:
left = 0
right = nCol
# remove the black border on both up and down side
up = 0
bottom = nRow
# for i in range(0, nRow):
# if src[i, :].mean() <= thres:
# up = i + 1
# else:
# break
#
# for i in range(nRow - 1, -1, -1):
# if src[i, :,].mean() <= thres:
# bottom = i
# else:
# break
black_idx = np.where(src.mean(axis=1) <= thres)[0].tolist()
for i in black_idx:
if up < i < nRow // 2:
up = i
elif nRow // 2 < i < bottom:
bottom = i
if bottom - up > 0:
top = up + shrink
bottom = bottom - shrink
else:
top = 0
bottom = nRow
return (left, top, right, bottom)
def det_video_black_border(video_path):
video = VideoFileClip(video_path)
duration = video.duration
test_duration = 600
video = video.subclip(
t_start=duration / 2 - test_duration / 2, t_end=duration / 2 + test_duration / 2
)
frame_num = 0
for frame in video.iter_frames(fps=1):
frame = frame.astype(np.int64)
if frame_num == 0:
frame_sum = frame
else:
frame_sum += frame
frame_num += 1
frame = frame_sum / frame_num
return det_image_black_border(frame, 5, 0)
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