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一分钟完成验证This is my ad video project
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Turn one product photo into a 15-second 9:16 AI ad video: AI motion, an AI-written script, voice-over (Hindi, English or Bangla), animated captions, background music and a closing call-to-action card, on the free Google Colab T4 GPU.
Website: https://advvideo4you.vercel.app
Notebook: colab/Advvideo4you_AI_Ad_Generator.ipynb
Layout preview rendered by this project's own FFmpeg commands over a placeholder photo (not an AI clip). Your video uses your photo and the Wan2.1 clip.查看完整 README ↗Turn one product photo into a 15-second 9:16 AI ad video: AI motion, an AI-written script, voice-over (Hindi, English or Bangla), animated captions, background music and a closing call-to-action card, on the free Google Colab T4 GPU.
Website: https://advvideo4you.vercel.app
Notebook: colab/Advvideo4you_AI_Ad_Generator.ipynb
Layout preview rendered by this project's own FFmpeg commands over a placeholder photo (not an AI clip). Your video uses your photo and the Wan2.1 clip.
advvideo-launch.json, and opens the notebook. Nothing is uploaded to a server.Runtime -> Run all (T4 GPU; if it is not selected: Runtime -> Change runtime type -> T4 GPU).advvideo-launch.json. That is the only click. (You can upload just a photo instead; the notebook then asks for the name, language and CTA.)Estimated time: first run 15–25 minutes (about 22 GB of models download once), later runs 5–8 minutes. These are estimates, not measurements; see Read this first.
Colab cannot receive parameters through a link, which is why settings travel in the launch file.
| Start Free dialog | How it works |
|---|---|
+faststart.drawtext on rectangular boxes. An SRT file is saved too.python -m advvideo.pipeline --prefetch)./content (or in your Drive with CACHE_TO_DRIVE).TEST_REPORT.md lists exactly what was and was not tested.THIRD_PARTY_LICENSES.md.script.json is saved next to the video) before publishing.| Path | Purpose |
|---|---|
index.html | The website: single static file, no build step |
colab/Advvideo4you_AI_Ad_Generator.ipynb | One Run-all cell: upload, background download, install, run the pipeline, download |
advvideo/spec.py | Output format (480×832, 15 s, 30 fps, 3 s closing card) |
advvideo/config.py | Launch-file format, validation, upload classification |
advvideo/script.py, llm_worker.py | Script generator (LLM + validation + templates) |
advvideo/voice.py, tts_worker.py | Piper voices, licences, 15-second timeline, voice mixing |
advvideo/captions.py | SRT, wrapping, rounded animated captions, closing card (ASS, drawtext fallback) |
advvideo/music.py | Synthesised background music, level matching to the voice |
advvideo/render.py | FFmpeg commands (loop, zoom/pan, captions, audio mix) and output checks |
advvideo/wan_launcher.py | Wan2.1 VACE on a T4 (patches applied in memory) |
advvideo/pipeline.py | Orchestration and --prefetch; the GPU stage runs alongside the audio work |
tests/ | Logic tests (pytest style, plain assert) |
docs/screenshots/ | Screenshots used in this README |
TEST_REPORT.md | What was tested, how, and what was not |
vercel.json, favicon.*, og.png, robots.txt, sitemap.xml | Static-site config and SEO |
pip install numpy pillow pytest
python -m pytest tests
The site deploys to Vercel from main with no build step. The notebook clones this repository at run time, so pushing to main updates it.
See VERSION, CHANGELOG.md and RELEASE_NOTES.md.
Code: MIT (see LICENSE). Models, voices, fonts and music carry their own licences, listed in THIRD_PARTY_LICENSES.md. The screenshots in docs/screenshots/ are original to this project (the placeholder product is an illustration drawn by code).