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GeeksforGeeks
geeksforgeeks.org › python › python-process-images-of-a-video-using-opencv
Python - Process images of a video using OpenCV - GeeksforGeeks
June 4, 2024 - DSA Python · Data Science · NumPy · Pandas · Practice · Django · Flask · Last Updated : 4 Jun, 2024 · Processing a video means, performing operations on the video frame by frame.
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D-Lab
dlab.berkeley.edu › news › processing-videos-python-opencv
Processing Videos in Python with OpenCV | D-Lab
November 28, 2023 - I am using a video from a camera ... this video is called “beetle_flight.avi”. We can use cv2.VideoCapture() function to create an object that represents the video in Python and work with the video file....
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Medium
medium.com › @kapildevkhatik2 › advanced-image-and-video-processing-techniques-using-python-549fb1cf224e
Advanced Image and Video Processing Techniques using Python | Computer Vision & Deep Learning Applications | Medium
March 11, 2023 - It can be used to read and write video files, add audio tracks, apply filters and effects, and more. MoviePy is built on top of other scientific Python libraries, such as NumPy, Pillow, and imageio, and is designed to be easy to use and customize. PyAV: PyAV is a Python wrapper for the FFmpeg multimedia library, which provides a range of functions for encoding, decoding, and processing audio and video data.
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Mike Polinowski
mpolinowski.github.io › development › python › python - video processing with opencv
Python - Video Processing with OpenCV | Mike Polinowski
This code will detect faces, and use the detected coordinates to draw a bounding box around them. These edited frames are then stashed in a new video file:
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GitHub
github.com › topics › video-processing
video-processing · GitHub Topics · GitHub
video-processing speech-recognition chinese speech-to-text transcription gradio video-editing asr content-creation video-transcription subtitles-generator ai-tools video-subtitles llm paraformer funasr ai-video-editing auto-subtitles whisper-alternative funclip ... Remove visible and invisible AI watermarks and provenance metadata from images and video. Python library and CLI for SynthID, C2PA, EXIF, IPTC, XMP, and common generative-AI marks.
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OpenCV
opencv.org › home › news › reading and writing videos using opencv
Reading and Writing Videos using OpenCV
March 28, 2025 - Writing Videos: The VideoWriter() function enables saving processed frames into a new video file with customizable resolution, frame rate, and encoding format. Practical Implementations: We provided Python and C++ code examples for reading videos from files, webcams, and image sequences, along with displaying videos frame by frame.
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Cloudinary
cloudinary.com › home › python video processing: 6 useful libraries and a quick tutorial
Python Video Processing: 6 Useful Libraries and a Quick Tutorial | Cloudinary
April 26, 2026 - Widely used by developers and ... When used with Python, OpenCV simplifies video processing through its intuitive API, allowing developers to read, modify, and analyze video frames efficiently....
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Reddit
reddit.com › r › learnpython › comments › ucx3p › python_video_processing
Python Video Processing? : r/learnpython
Subreddit for posting questions and asking for general advice about all topics related to learning python.
Find elsewhere
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Analytics Vidhya
analyticsvidhya.com › home › deep learning tutorial to calculate the screen time of actors in any video (with python codes)
Deep Learning Tutorial to Calculate the Screen Time of Actors in any Video (with Python codes)
October 15, 2024 - A complete deep learning tutorial for video analysis using python. This article will help you understand how to use deep learning on video data.
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Quora
quora.com › How-can-I-do-real-time-video-processing-and-streaming-processed-video-in-Raspberry-Pi-using-Python-language
How to do real time video processing and streaming processed video in Raspberry Pi using Python language - Quora
Answer (1 of 2): Real-time video processing can be done using Raspberry Pi and Python. The tools that you will be needing is a library called as OpenCV (import cv2) for python and a pi camera or webcam for the raspberry pi. The workaround tutorial on how to install and do is provided by Adrian R...
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DeepLearning.AI
deeplearning.ai › courses › ai-python-for-beginners
AI Python for Beginners - DeepLearning.AI
August 7, 2024 - You’ll be amazed at how quickly you can go from writing your first line of code to creating AI-powered applications that can process and analyze real-world data. This course is for anyone curious about AI and programming with Python, from complete beginners learning to code for the first time to professionals seeking to boost productivity and learn how to properly integrate AI into their coding process.
Top answer
1 of 7
68

After reading the documentation of VideoCapture. I figured out that you can tell VideoCapture, which frame to process next time we call VideoCapture.read() (or VideoCapture.grab()).

The problem is that when you want to read() a frame which is not ready, the VideoCapture object stuck on that frame and never proceed. So you have to force it to start again from the previous frame.

Here is the code

import cv2

cap = cv2.VideoCapture("./out.mp4")
while not cap.isOpened():
    cap = cv2.VideoCapture("./out.mp4")
    cv2.waitKey(1000)
    print "Wait for the header"

pos_frame = cap.get(cv2.cv.CV_CAP_PROP_POS_FRAMES)
while True:
    flag, frame = cap.read()
    if flag:
        # The frame is ready and already captured
        cv2.imshow('video', frame)
        pos_frame = cap.get(cv2.cv.CV_CAP_PROP_POS_FRAMES)
        print str(pos_frame)+" frames"
    else:
        # The next frame is not ready, so we try to read it again
        cap.set(cv2.cv.CV_CAP_PROP_POS_FRAMES, pos_frame-1)
        print "frame is not ready"
        # It is better to wait for a while for the next frame to be ready
        cv2.waitKey(1000)

    if cv2.waitKey(10) == 27:
        break
    if cap.get(cv2.cv.CV_CAP_PROP_POS_FRAMES) == cap.get(cv2.cv.CV_CAP_PROP_FRAME_COUNT):
        # If the number of captured frames is equal to the total number of frames,
        # we stop
        break
2 of 7
31

Use this:

import cv2
cap = cv2.VideoCapture('path to video file')
count = 0
while cap.isOpened():
    ret,frame = cap.read()
    cv2.imshow('window-name', frame)
    cv2.imwrite("frame%d.jpg" % count, frame)
    count = count + 1
    if cv2.waitKey(10) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows() # destroy all opened windows
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Cloudinary
cloudinary.com › home › creating a video from images using python
Creating a Video from Images Using Python | Cloudinary
November 17, 2025 - FFmpeg: A powerful command-line tool with Python bindings available. FFmpeg is renowned for its versatility and extensive format support, making it suitable for complex video processing tasks.
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GeeksforGeeks
geeksforgeeks.org › python › opencv-python-tutorial
OpenCV Tutorial in Python - GeeksforGeeks
OpenCV (Open Source Computer Vision Library) is an open-source computer vision and machine learning library. It allows us to process images and videos, detect objects, faces and even handwriting. This tutorial will guide us through image and video processing from the basics to advanced topics using Python and OpenCV.
Published: July 12, 2025
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GitHub
github.com › abhiTronix › vidgear
GitHub - abhiTronix/vidgear: A High-performance cross-platform Video Processing Python framework powerpacked with unique trailblazing features :fire: · GitHub
"VidGear is a cross-platform High-Performance Framework that provides an one-stop Video-Processing solution for building complex real-time media applications in python."
Author: abhiTronix
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FastAPI
fastapi.tiangolo.com › advanced › custom-response
Custom Response - HTML, Stream, File, others - FastAPI
import anyio from fastapi import FastAPI from fastapi.responses import StreamingResponse app = FastAPI() async def fake_video_streamer(): for i in range(10): yield b"some fake video bytes" await anyio.sleep(0) @app.get("/") async def main(): return StreamingResponse(fake_video_streamer())
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NVIDIA Developer
developer.nvidia.com › blog › whats-new-in-pynvvideocodec-2-0-for-python-gpu-accelerated-video-processing
What’s New in PyNvVideoCodec 2.0 for Python GPU-Accelerated Video Processing | NVIDIA Technical Blog
September 18, 2025 - Powerful hardware-accelerated video processing in Python just got easier. PyNvVideoCodec is an NVIDIA Python-based library for GPU-accelerated video encoding, decoding, and transcoding.
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Medium
medium.com › data-science › faster-video-processing-in-python-using-parallel-computing-25da1ad4a01
Faster Video Processing in Python using Parallel Computing | by Sabina Pokhrel | TDS Archive | Medium
April 9, 2020 - In this post, we will use FFmpeg to join multiple video files. To install ffmpeg, use the following apt-get command: ... Let’s import the required python libraries. ... subprocess: to start new processes, connect to their input/output/error pipes, and obtain their return codes.
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Educative
educative.io › answers › video-processing-using-opencv
Video processing using OpenCV
In video processing, each frame is processed individually or in sequence. OpenCV provides methods to access, manipulate, and analyze individual frames, such as resizing, cropping, flipping, and rotating them.