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v0.8.5 - Verified end-to-end with isolated cache

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@Rinne414 Rinne414 released this 29 May 14:10
· 48 commits to main since this release
v0.8.5
7c8d706

v0.8.5 — Verified working end-to-end

This time I tested it before shipping. Setup that mirrors the .exe environment (renamed venv torch + numpy to invisible names so only the downloaded cache could provide them):

activate_runtime: ok=True
torch from: %LOCALAPPDATA%/vid2dataset/gpu_runtime/torch
CUDA: True (NVIDIA GeForce RTX 3090)
numpy from: cache
gpu pipeline: True
Real extraction: ran full pipeline with gpu_accel=True
  -> scene detect -> ffmpeg keyframes -> auto-quality
  -> GPU SSIM filter -> bucket resize -> done

Sorry for the v0.8.3 / v0.8.4 churn. 對前兩個版本接連失敗道歉。

What was wrong with v0.8.4

  1. numpy never actually got into the download list. My v0.8.4 edit relied on a string match that silently failed. Release notes claimed numpy was bundled — it wasn't. You hit the same activation failure plus a misleading patch note.

  2. The fix that DID land made things worse. v0.8.4's sys.path.insert(0, cache) shadowed every PyInstaller-bundled dep. Even when numpy WOULD have been in cache, the cache's typing_extensions==4.12.2 overrode the .exe's bundled 4.13+. Result: ImportError: cannot import name 'Sentinel' from 'typing_extensions' when loading gpu_filters.

What v0.8.5 actually fixes

  • numpy 2.1.3 is in _PYPI_DEPS (verified by re-reading the list after edit).
  • activate_runtime() uses sys.path.append(cache) instead of insert. PyInstaller's bundled site-packages win for shared deps (typing_extensions, jinja2, etc.); torch is only in cache so it's found there.
  • activate_runtime() returns the real error string. If anything still fails for you, the dialog will tell you the actual ImportError instead of "无法载入".
  • RUNTIME_VERSION bumped, so old cache (without numpy) auto-refreshes.

Test before downloading

I ran the full pipeline (gpu_accel=True) in an environment where the only torch reachable was the cache copy. CUDA matmul, GPU SSIM filter, and the whole extractor ran clean.

Update

  1. Click 检查更新 / Check for Updates in the app
  2. Tick GPU 加速 — old cache will auto-refresh, this time with numpy
  3. Activation dialog should say "GPU runtime ready"

Download

  • vid2dataset.exe (151 MB)
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