-
Notifications
You must be signed in to change notification settings - Fork 0
/
transfer training dataset.py
38 lines (35 loc) · 1.15 KB
/
transfer training dataset.py
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
# -*- coding: utf-8 -*-
"""
Created on Fri Mar 13 22:25:10 2020
@author: Chirag
"""
import numpy as np
import matplotlib.pyplot as plt
import pandas as pd
import cv2
import glob
import math
files = [file for file in glob.glob("UCF-101/*")]
sub_files = []
for file in files:
print(file)
sub_files = [ sub_file for sub_file in glob.glob(file + "/*.*")]
sub_files = sub_files[:-1]
counter = 0
for sub_file in sub_files:
counter += 1
count = 0
cap = cv2.VideoCapture(sub_file) # capturing the video from the given path
frameRate = cap.get(5) #frame rate
x=1
direc = sub_file.split("\\")[1]
while(cap.isOpened()):
frameId = cap.get(1) #current frame number
ret, frame = cap.read()
if (ret != True):
break
if (frameId % math.floor(frameRate) == 0):
# storing the frames in a new folder named train_1
filename = "UCF 101 (me)\\Training\\" + direc + "\\Training_frame%d%d.jpg" %(counter,count) ;count+=1
cv2.imwrite(filename, frame)
cap.release()