huchukatoandDevin
970f51649b
- Add RIFE v4.25 architecture support in rife_arch.py (Head with 16/4 channels, 5 IFBlocks with c=192/128/96/64/32, scale_list [16,8,4,2,1], no ensemble) - Add rife425.pth to export_onnx.py with HF fallback URL - Update load_rife_config.json: dropdown now only shows rife425 and rife49 (removed rife47/48/417/426/sudo_rife4 that never worked) - Set rife425 as default - Make TORCH_DEVICE fallback to CPU for ONNX export on non-CUDA - Pin polygraphy==0.49.26 for TensorRT 10.15.1 compatibility Generated with [Devin](https://devin.ai) Co-Authored-By: Devin <158243242+devin-ai-integration[bot]@users.noreply.github.com>
25 lines
978 B
JSON
25 lines
978 B
JSON
{
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"model": {
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"options": [
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"rife49_ensemble_True_scale_1_sim",
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"rife425_ensemble_False_scale_1_sim"
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],
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"default": "rife425_ensemble_False_scale_1_sim",
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"tooltip": "RIFE models for video frame interpolation. rife425 (v4.25) is the recommended default for diffusion-generated video. rife49 (v4.9) is the stable legacy option."
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},
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"precision": {
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"options": ["fp16", "fp32"],
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"default": "fp16",
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"tooltip": "Precision to build the tensorrt engines. Loaded from config."
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},
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"resolution_profile": {
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"options": ["small", "medium", "large"],
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"default": "small",
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"tooltip": "Resolution range for TensorRT engine. Small: 384-1080px, Medium: 672-1312px, Large: 720-1920px. Smaller ranges use less VRAM."
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},
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"resolution_profiles": {
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"small": { "min": 384, "opt": 720, "max": 1080 },
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"medium": { "min": 672, "opt": 1080, "max": 1312 },
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"large": { "min": 720, "opt": 1440, "max": 1920 }
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}
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} |