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Merge remote-tracking branch 'origin/develop' into add-mypy-strict-typecheck
# Conflicts: # app.py # postprocess/interpolation.py # postprocess/upscale/upscale.pyc8ec0f7 -
Build a tensor-only RIFE -> upscale pipeline (#53)
Interpolation can now hand upscale (C,H,W) fp16 GPU tensors directly instead of round-tripping every frame through CPU numpy in between, when both stages run in the same @spaces.GPU allocation. The "no upscale" and "no interpolation" paths are unchanged. Adds a print_frames_info log line after interpolation so the handoff mode (tensor vs. numpy) is visible in production logs. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>fed6bc3
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Add mypy --strict type-check CI gate on every PR
Annotates the previously-untyped functions in app.py, model/pipeline.py, and postprocess/interpolation.py, fixes the couple of real bugs strict type-checking surfaced (deprecated Image.LANCZOS constant, an int-or-None mixing in preview_effect, a numpy float**float Any leak), and adds a pyproject.toml mypy config that exempts vendored third-party files instead of relaxing strictness project-wide. Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01CRfYRYPEtM8UA6mtHoKL422682589 -
Pre-download RIFE/upscale weights at startup instead of inside @spaces.GPU (#22)
Unverified signatureThe RIFE and 4xLSDIRCompact weight fetches are pure network/disk I/O with no CUDA dependency, but were only downloaded lazily on first use inside the metered @spaces.GPU allocation — costing a few seconds of ZeroGPU quota on every cold container start. Move both fetches to app startup (alongside load_pipeline()), mirroring how the main video model is already preloaded. Claude-Session: https://claude.ai/code/session_011keM1seSWsBZqPHrzKTeCG Co-authored-by: Claude Sonnet 5 <noreply@anthropic.com>7123409
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Add RIFE frame interpolation stage (FR-3, FR-5, ID-1)
postprocess/interpolation.py: RIFE v4.26 (thornmaze/RIFE), fp16, 2x/4x/8x multiplier, runs on GPU inside the same @spaces.GPU allocation as generation, wired into app.py's "Video Fluidity" dropdown. Vendors model/warplayer.py, model/loss.py, and model/pytorch_msssim/ from hzwer/Practical-RIFE (MIT) since the downloaded train_log/RIFE_HDv3.py module imports from a sibling `model` package at load time. Closes #5 Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>f5e3ffa