The following code will loop the video, perform some processing and write the output to a video file.
import cv2from google.colab.patches import cv2_imshowvideo_path = "./video.mp4"cap = cv2.VideoCapture(video_path)if cap.isOpened(): width = int(cap.get(cv2.CAP_PROP_FRAME_WIDTH)) height = int(cap.get(cv2.CAP_PROP_FRAME_HEIGHT)) res=(int(width), int(height)) # this format fail to play in Chrome/Win10/Colab # fourcc = cv2.VideoWriter_fourcc(*'MP4V') #codec fourcc = cv2.VideoWriter_fourcc(*'H264') #codec out = cv2.VideoWriter('output.mp4', fourcc, 20.0, res) frame = None while True: try: is_success, frame = cap.read() except cv2.error: continue if not is_success: break # OPTIONAL: do some processing # convert cv2 BGR format to RGB image = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) out.write(image) out.release() # OPTIONAL: show last image if frame: cv2_imshow(frame)cap.release()Show the output video (this will not work for large video file)
from IPython.display import HTMLfrom base64 import b64encodemp4 = open(video_path, "rb").read()data_url = "data:video/mp4;base64," + b64encode(mp4).decode()HTML(f"""<video width=400 controls> <source src="{data_url}" type="video/mp4"></video>""")You could display each frame via method such as cv2_imshow, but you will have a long list of images.
You could perform a show and clear, but you will have some performance issues as the UI doesn't display the output fast enough (will have many skipped frames)
from IPython.display import clear_outputfrom google.colab.patches import cv2_imshowcv2_imshow(image)clear_output(wait=True)