Automating the cutting of long videos into short highlight

Automating the cutting of long videos into short highlights

The task:
The client needed to develop software for automatically cutting long videos into short highlights. The main focus was to automatically detect the beginning and end of the desired fragments without pre-setting time codes.

Solution: The OpenCV library was used to implement the project. It allowed us to:

- Identify moments with a black screen in the video that served as dividers between key scenes.
- Detect the timecodes of the beginning and end of each fragment based on the analysis of the video content.

Technical Implementation:

Video processing:
- Videos were uploaded through the Django admin panel.
- Using OpenCV, we analyzed the frames and identified the necessary sections for cutting.

Result:
- Each selected fragment was saved to a separate video file.
- All cut fragments were automatically packed to a ZIP-archive.

Interface:
- The Django admin panel was used to easily upload the source video.
- After processing, the user was able to download the ZIP-archive with the cut video fragments.
Technologies:

- Python to develop the main logical functionality.
- OpenCV for video processing and frame analysis.
- Django to create an administrative panel and manage file uploads/downloads.

Result:
The software successfully automated the video cutting process. The client no longer needed to manually write down time codes, as the necessary moments were automatically determined based on visual analysis. The solution saved a significant amount of time and simplified the process of working with video.

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