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AI-Video-Cropper is a Python-based tool that leverages the power of GPT-4 (OpenAI's language model) to automatically analyze videos, extract the most interesting sections, and crop them for improved viewing experience. This project combines the capabilities of GPT-4, FFmpeg, and OpenCV to automate the process of identifying highlights in videos

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#AI-Shorts-Creator! 🎥✂️ (WIP, You Might face some Bugs)

AI-Shorts-Creator is a powerful tool designed for content creators, podcasters, and video enthusiasts to effortlessly extract captivating segments from their videos. Leveraging the advanced language model GPT-4, this innovative solution intelligently analyzes video transcripts to identify the most viral and exciting moments. By harnessing the capabilities of FFmpeg and OpenCV, AI-Shorts-Creator automatically crops videos, allowing you to focus on the key highlights and provide an enhanced viewing experience.

AI-Shorts-Creator is a powerful tool designed to:

  • Automatically extract captivating segments from videos.
  • Identify the most viral and exciting moments using GPT-4.
  • Crop videos to emphasize key highlights with precise face detection.
  • Streamline video editing and save time by eliminating manual searching.
  • Work seamlessly with various video formats for maximum compatibility.
  • Enhance the viewing experience for your audience with perfectly cropped highlights.

Examples:

Source Video : https://www.youtube.com/watch?v=NHaczOsMQ20 thumbnail

Output Shorts:

Demo GIF 1 Demo GIF 2 Demo GIF 3
output_shorts.mp4

Get started with AI-Shorts-Creator today and unlock the potential of your videos like never before!

Requirements

  • Python 3.x
  • pytube library (install with pip install pytube)
  • opencv-python library (install with pip install opencv-python)
  • openai library (install with pip install openai)
  • youtube-transcript-api library (install with pip install youtube-transcript-api)
  • FFmpeg (install according to your operating system)

Usage

  1. Install the required libraries by running the following command:
pip install -r requirements.txt
  1. Install FFmpeg by following the installation instructions for your operating system. Make sure the ffmpeg command is accessible from the command line.

  2. Set up your OpenAI API key by replacing openai.api_key = '' with your actual OpenAI API key.

  3. Modify the video_id variable in the main() function to specify the YouTube video you want to process.

  4. Run the script:

python auto_cropper.py

The script will download the YouTube video, analyze its transcript using OpenAI's GPT-4, extract the best sections based on the analysis, crop the video using FFmpeg, and apply face detection using OpenCV to further refine the cropping.

Additional Information

  • The download_video(url, filename) function downloads a YouTube video by providing the URL and specifying the filename.
  • The segment_video(response) function segments the video into interesting sections based on a transcript analysis using OpenAI's GPT-4 model.
  • The detect_faces(video_file) function uses face detection to identify faces in a video file.
  • The crop_video(faces, input_file, output_file) function crops the video around the detected faces using FFmpeg.
  • The is_talking_in_batch(frames) function analyzes the lip movement or facial muscle activity within a batch of frames to determine if talking behavior is present.
  • The adjust_focus(frame, talking) function applies visual effects or adjustments to emphasize the speaker in the frame.

Please note that the GPT-4 model and transcript analysis functionality in the provided code are simulated and not fully functional. You would need a valid OpenAI API key and a working GPT-4 model to perform transcript analysis.

About

AI-Video-Cropper is a Python-based tool that leverages the power of GPT-4 (OpenAI's language model) to automatically analyze videos, extract the most interesting sections, and crop them for improved viewing experience. This project combines the capabilities of GPT-4, FFmpeg, and OpenCV to automate the process of identifying highlights in videos

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  • Jupyter Notebook 88.2%
  • Python 11.8%