--- license: other tags: - stereo-matching - depth-estimation - computer-vision --- # Stereo Matching Model Weights (mirror) Mirror of three stereo-matching model checkpoints, re-hosted on Hugging Face so they can be pulled from behind a corporate firewall that blocks Google Drive. All weights are copied verbatim from their original public sources — credit and licensing belong to the original authors. ## Contents ### `foundationstereo/` — Fast-FoundationStereo Source: Google Drive folder `1HuTt7UIp7gQsMiDvJwVuWmKpvFzIIMap`. Each timestamped folder is one complete model (`model_best_bp2_serialize.pth` + `cfg.yaml`): | Folder | Notes | |-------------|-----------------------------------------| | `23-36-37` | Most accurate (PyTorch 49.4 ms / TRT 23.4 ms) | | `20-26-39` | Middle | | `20-30-48` | Fastest (PyTorch 38.4 ms / TRT 16.6 ms) | | `15-44-51` | Extra model included in the source folder | `onnx/` holds pre-exported ONNX models for `20_26_39`, `20_30_48`, `23_36_37` at 320x736 / 576x960 and 4 / 8 iterations. ### `liteanystereo/` — LiteAnyStereo Source: Google Drive folder `1UvDx296pVk7pC2rozKIpQF_EXcOleZOB`. - `LAS1/` — LAS1 checkpoints, incl. `LiteAnyStereo.pth` (not available on HF elsewhere). - `LAS2/` — LAS2 S/M/H/L (same as `tomtomtommi/LiteAnyStereoV2`, included for completeness). ### `mobilestereonet/` — MobileStereoNet Source: individual Google Drive file IDs (see MobileStereoNet repo). 2D and 3D variants, trained on different combinations of SceneFlow (SF), DrivingStereo (DS) and KITTI2015. `*DS+KITTI2015*` and `*SF+DS+KITTI2015*` are the best on KITTI2015 val. ## Download example ```python # NOTE: on the corporate network, add these two lines BEFORE importing # huggingface_hub, or the TLS interception makes SSL verification fail: import truststore truststore.inject_into_ssl() from huggingface_hub import snapshot_download, hf_hub_download # whole repo snapshot_download(repo_id="Miayan/stereo-matching-weights", local_dir="./weights") # single file hf_hub_download(repo_id="Miayan/stereo-matching-weights", filename="foundationstereo/23-36-37/model_best_bp2_serialize.pth", local_dir="./weights") ```