This gist describes serialising a video, frame by frame, and then reconstructing the image using opencv and ffmpeg

ff_serialiser.py

import subprocess as sp
import cv2 as cv
import numpy as np
import ffmpeg

probe = ffmpeg.probe('/home/jyotendra/Videos/pandas.mp4')
video_info = next(s for s in probe['streams'] if s['codec_type'] == 'video')
width = int(video_info['width'])
height = int(video_info['height'])
num_frames = int(video_info['nb_frames'])


command = ["ffmpeg", "-i", "/home/jyotendra/Videos/pandas.mp4", "-f", "image2pipe", "-pix_fmt", "rgb24", "-vcodec", "rawvideo", "-"]

pipe = sp.Popen(command, stdout = sp.PIPE, bufsize=10**8)

for i in [*range(300)]:
    raw_image = pipe.stdout.read(width * height * 3)
    # print("img" + str(raw_image) + "\n")
    image = np.fromstring(raw_image, dtype='uint8')
    if image.size > 0:
        image = image.reshape((height, width, 3))
        # image = cv.cvtColor(image, cv.COLOR_RGB2BGR)
    cv.imwrite("test"+str(i)+".jpg", image)
    # print(image)
    pipe.stdout.flush()

ff_serialiser_resized.py

import subprocess as sp
import cv2 as cv
import numpy as np
import ffmpeg

probe = ffmpeg.probe('/home/jyotendra/Videos/pandas.mp4')
video_info = next(s for s in probe['streams'] if s['codec_type'] == 'video')
width = int(video_info['width'])
height = int(video_info['height'])
num_frames = int(video_info['nb_frames'])


command = ["ffmpeg", "-i", "/home/jyotendra/Videos/pandas.mp4", "-vf", "scale=420:360", "-f", "image2pipe", "-pix_fmt", "rgb24", "-vcodec", "rawvideo", "-"]

pipe = sp.Popen(command, stdout = sp.PIPE, bufsize=10**8)

for i in [*range(300)]:
    raw_image = pipe.stdout.read(420 * 360 * 3)
    # print("img" + str(raw_image) + "\n")
    image = np.fromstring(raw_image, dtype='uint8')
    if image.size > 0:
        image = image.reshape((360, 420, 3))
        image = cv.cvtColor(image, cv.COLOR_RGB2BGR)
    cv.imwrite("test"+str(i)+".jpg", image)
    # print(image)
    pipe.stdout.flush()