#-*-?coding:?utf-8?-*-
‘‘‘
functions?to?extract?VGG?（or?any?other）?features?from?videos:
For?each?video:
1.?extract?frames?from?video?（using?Opencv）
2.?select?n?（n=80?in?this?case）?frames
3.?rezie?and?crop?the?selected?frames
4.??For?each?frames:
????1.?feed?to?the?VGG-16?model?（providied?with?pre-trained?weight?using?Caffe）
????2.?obtain?the?VGG?features:?1*4096
5.?obtain?the?VGG?features?of?all?n?frames?and?store?the?result?as?an?array?（shape:?n*4096）
‘‘‘
import?sys
import?cv2
import?os
import?numpy?as?np
import?skimage
import?tensorflow?as?tf
import?os
import?numpy?as?np
import?torch
import?torch.nn
import?torchvision.models?as?models
from?torch.autograd?import?Variable?
import?torch.cuda
import?torchvision.transforms?as?transforms
from?PIL?import?Image

#os.environ[“CUDA_DEVICE_ORDER“

?屬性????????????大小?????日期????時間???名稱
-----------?---------??----------?-----??----

?????文件???????5726??2019-02-22?16:01??extract_RGB_feats.py

?????文件???????5024??2019-02-22?18:52??feats_exact實際應用.py

?????文件??????33677??2019-02-26?10:25??model_RGB.py

?????文件??????34076??2019-02-28?10:13??model_RGB實際應用.py

?????文件????????893??2019-02-22?09:53??resnet101_feat_exact.py

-----------?---------??----------?-----??----

????????????????79396????????????????????5