| license: mit | |
| library_name: libreyolo | |
| tags: | |
| - depth-estimation | |
| - monocular-depth | |
| - midas | |
| # LibreMiDaSs-depth | |
| MiDaS EfficientNet-Lite3 (MiDaS v2.1 small, 256 px) monocular depth model, repackaged in LibreYOLO checkpoint format. | |
| ## Source | |
| Derived from [isl-org/MiDaS](https://github.com/isl-org/MiDaS), release asset | |
| `midas_v21_small_256.pt`. | |
| Copyright (c) Intel ISL. Licensed under the MIT License. | |
| ## Modifications | |
| State-dict key remapping only. Learned parameters are unchanged. | |
| See `weights/convert_midas_weights.py` in the | |
| [LibreYOLO source repository](https://github.com/LibreYOLO/libreyolo). | |
| ## A note on the training data | |
| MiDaS was trained on a mixture of twelve datasets, several of which carry | |
| non-commercial terms of their own. LibreYOLO redistributes these weights under | |
| the MIT licence its publisher applied to them. If your use is commercial, | |
| satisfy yourself about the training-data terms before relying on it. | |
| ## Usage | |
| ```python | |
| from libreyolo import LibreYOLO | |
| model = LibreYOLO("LibreMiDaSs-depth.pt") | |
| depth = model.predict("image.jpg")[0].depth_map | |
| ``` | |
| ## License | |
| MIT License. See the [`LICENSE`](./LICENSE) and [`NOTICE`](./NOTICE) files in | |
| this repository. | |