soCzech/TransNetV2

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1027 stars · 149 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

TransNet V2 is a deep neural network for shot boundary detection in videos, achieving state-of-the-art results on benchmarks like ClipShots and BBC Planet Earth. The repository provides pretrained models for inference (TensorFlow and PyTorch) plus training code to replicate the paper's experiments.

Use cases

• detect shot transitions in a video
• split a movie into scenes automatically
• find hard cuts and gradual transitions in video files
• segment video archives into shots for indexing
• run pretrained shot detection model in python
• compare shot boundary detection methods

When to choose

• you need accurate, fast shot boundary detection with a pretrained model
• you want state-of-the-art F1 scores on standard shot detection benchmarks
• you need both TensorFlow and PyTorch inference options
• you want to reproduce or extend published shot detection research

When to avoid

• you need general video editing or transcoding rather than shot detection
• you want a maintained product with frequent updates and support
• you cannot use GPU acceleration for inference
• you need audio-based scene segmentation

Facets

library · maturity stable

computer-vision video-processing deep-learning machine-learning computer-vision machine-learning deep-learning python shot-boundary-detection scene-detection video-segmentation pytorch tensorflow pretrained-model research-code video gpu docker linux

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markdown · JSON · MCP: product_card(name="soCzech/TransNetV2")