Models/VideoProcessor.py

import cv2
import numpy as np

class VideoProcessor:
    def __init__(self, mp4):
        self.mp4 = mp4
        self.video_frames = []

    def extract_frames(self, ratio):
        # Extracts frames from video
        # ratio: ratio of frames to extract
        vid_cap = cv2.VideoCapture(self.mp4)
        frame_count = int(vid_cap.get(cv2.CAP_PROP_FRAME_COUNT))
        frame_number = 0
        while vid_cap.isOpened():
            ret, frame = vid_cap.read()
            if ret:
                if frame_number % ratio == 0:
                    self.video_frames.append(frame)
                frame_number += 1
            else:
                break
        
    def resize_and_normalize_frames(self, width, height, normalizing_const=255.0):
        # Resizes frames
        # width: width of frame
        # height: height of frame
        resized_normal_frames = []
        for frame in self.video_frames:
          frame = cv2.resize(frame, (width, height))
          frame = frame.astype(np.float32) / normalizing_const
          resized_normal_frames.append(frame)
        self.video_frames = resized_normal_frames

    def get_frames(self):
        # Returns: numpy array of frames
        if self.video_frames != []:
            return np.array(self.video_frames)
        else:
            return None