blob: eeaa6bb0e62533835e4ec1ad9e0cbb4d842aa406 (
plain)
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
|
import paddlehub as hub
from PIL import Image
import os
import cv2
import matplotlib.pyplot as plt
import matplotlib.image as mpimg
import numpy as np
def video2jpg(video_file, output_path):
'''
将视频文件video_file每一帧转成图片保存到output_path文件夹
'''
try:
os.makedirs(output_path) # 创建输出文件夹
except:
print()
# 读取视频文件
cap = cv2.VideoCapture(video_file)
n_frames = int(cap.get(cv2.CAP_PROP_FRAME_COUNT))
num = 0
while True:
ret, frame = cap.read()
if ret:
cv2.imwrite('{}/{}-{}.jpg'.format(output_path, n_frames, num), frame)
num += 1
else:
break
cap.release() # 关闭视频
def humanseg(images):
# 装载模型
module = hub.Module(name="deeplabv3p_xception65_humanseg")
# 执行模型segmentation(抠图)命令
module.segmentation(data={"image": images}, visualization=True)
# for i, img in enumerate(images):
# print(i, img)
# result = module.segmentation(data={"image": [img]}, visualization=True)
def file_list(listdir):
im_list = []
imgs = os.listdir(listdir)
for img in imgs:
im_list.append(os.path.join(listdir, img))
return im_list
if __name__ == '__main__':
# video2jpg('vtest.avi', 'v2j')
img_list = file_list('./v2j')
humanseg(img_list)
|
