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README.md
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license: mit
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---
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license: mit
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---
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# Video → ZIP Caption Prep
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Input: a video file.
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Output: a `.zip` containing:
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- `frames/` sampled JPG frames
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- `transcription.txt` from ASR
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- `explanations.json` with per-frame captions
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- `manifest.json` summary
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## Models
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- ASR: `distil-whisper/distil-large-v3`
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- Vision captions: `Salesforce/blip-image-captioning-base`
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These are open-source on Hugging Face. GPU recommended. CPU works but slower.
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## How it works
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1) Extract audio with FFmpeg.
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2) Transcribe via Whisper pipeline.
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3) Sample frames every *N* seconds with OpenCV.
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4) Caption each frame with BLIP.
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5) Package outputs into a ZIP for downstream use.
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## Space usage
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1. Click **Upload video**.
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2. Adjust **Frame interval** or **Max frames** if needed.
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3. Press **Process**.
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4. Download the ZIP. Preview shows a few frames, transcript snippet, and first captions.
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## Local dev
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```bash
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pip install -r requirements.txt
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python app.py
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# or CLI:
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python runner.py --video path/to/video.mp4 --interval 2.0 --max_frames 150
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