AkaneTendo25/ayase-models
By AkaneTendo25 · ↓ 0 · ♥ 0 · Updated 2026-03-18
What's in this repo
This page lists the files in AkaneTendo25/ayase-models, including onnx_dover.onnx.
- 1 ONNX models (.onnx files)
- 33 files, including 13 .pth, 12 .md, 5 .pt, 1 .onnx, 1 .pkl
- Last updated 2026-03-18
ONNX files
| File | Size | Download |
|---|---|---|
| dover/onnx_dover.onnx | — | Download |
How to use
These ONNX files can be loaded with ONNX Runtime. To inspect a model graph, upload the file to the Netron viewer. Download links point to the original files on Hugging Face.
README
Ayase Models
Pre-downloaded model weights for Ayase modules that require non-HuggingFace downloads.
These models are hosted here because their original CDNs (dl.fbaipublicfiles.com, openaipublic.azureedge.net, GitHub releases) can be unreliable or blocked on some servers.
Structure
ayase-models/
├── dover/ # DOVER video quality assessment (ICCV 2023)
│ ├── DOVER.pth # 229 MB — Apache 2.0
│ └── convnext_tiny_1k_224_ema.pth # 110 MB — MIT
├── i2v_similarity/ # Image-to-Video similarity metrics
│ ├── ViT-B-32.pt # 338 MB — MIT (OpenAI CLIP)
│ ├── dinov2_vitb14_pretrain.pth # 331 MB — Apache 2.0 (Meta)
│ └── alex.pth # 6 KB — BSD-2 (LPIPS)
├── advanced_flow/ # RAFT optical flow (ECCV 2020)
│ ├── raft_large_C_T_SKHT_V2-ff5fadd5.pth # 21 MB — BSD-3
│ └── raft_small_C_T_V2-01064c6d.pth # 3.9 MB — BSD-3
├── fast_vqa/ # FAST-VQA quality assessment (ECCV 2022)
│ ├── FAST_VQA_3D_1_1.pth # 121 MB — MIT
│ ├── FAST_VQA_B_1_4.pth # 121 MB — MIT
│ └── FAST_VQA_M_1_4.pth # 105 MB — MIT
├── aesthetic_scoring/ # LAION aesthetic predictor
│ └── sac+logos+ava1-l14-linearMSE.pth # 3.5 MB — MIT
├── video_memorability/ # Video memorability estimation
│ └── dinov2_vits14_pretrain.pth # 84 MB — Apache 2.0 (Meta)
├── spectral/ # Spectral analysis
│ └── dinov2_vits14_pretrain.pth # 84 MB — Apache 2.0 (Meta)
├── trajan/ # Point tracking (CoTracker2)
│ └── cotracker2.pth # 194 MB — Apache 2.0 (Meta)
├── depth_map_quality/ # Monocular depth estimation
│ ├── dpt_swin2_tiny_256.pt # 164 MB — MIT (Intel ISL MiDaS)
│ └── midas_v21_small_256.pt # 82 MB — MIT (Intel ISL MiDaS)
└── depth_consistency/ # Temporal depth consistency
├── dpt_swin2_tiny_256.pt # 164 MB — MIT
└── midas_v21_small_256.pt # 82 MB — MIT
Total: ~2 GB
Models hosted on HuggingFace Hub (not included here)
These models are downloaded directly via transformers / open_clip and work without re-hosting:
| Module | HF Model | License |
|---|---|---|
| semantic_alignment | openai/clip-vit-base-patch32 | MIT |
| clip_temporal | openai/clip-vit-base-patch32 | MIT |
| captioning | Salesforce/blip-image-captioning-base | BSD-3 |
| sd_reference | stabilityai/stable-diffusion-xl-base-1.0 | CreativeML Open RAIL++-M |
| action_recognition | MCG-NJU/videomae-large-finetuned-kinetics | CC-BY-NC-4.0 |
| ocr_fidelity | PaddleOCR (self-managed) | Apache 2.0 |
License
Each subdirectory contains a LICENSE.md with attribution for the respective model weights. All models are redistributed under their original open-source licenses.
Files (33)
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