Instructions to use mnmly/anycalib-mlx with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- MLX
How to use mnmly/anycalib-mlx with MLX:
# Download the model from the Hub pip install huggingface_hub[hf_xet] huggingface-cli download --local-dir anycalib-mlx mnmly/anycalib-mlx
- Notebooks
- Google Colab
- Kaggle
- Local Apps Settings
- LM Studio
- Atomic Chat
| mlx-swift-AnyCalib | |
| Copyright 2026 Hiroaki Yamane | |
| This product includes software developed as a port of AnyCalib. | |
| -------------------------------------------------------------------------------- | |
| AnyCalib | |
| https://github.com/javrtg/AnyCalib | |
| Copyright (c) Javier Tirado-Garín and Javier Civera, I3A, University of Zaragoza | |
| Licensed under the Apache License, Version 2.0. | |
| "AnyCalib: On-Manifold Learning for Model-Agnostic Single-View Camera | |
| Calibration", ICCV 2025. | |
| The model architecture, camera models, on-manifold optimization, and the | |
| pretrained weights redistributed by this project all originate there. The | |
| Swift/MLX sources in Sources/MLXAnyCalib are a translation of that PyTorch | |
| implementation. | |
| -------------------------------------------------------------------------------- | |
| DINOv2 | |
| https://github.com/facebookresearch/dinov2 | |
| Copyright (c) Meta Platforms, Inc. and affiliates. | |
| Licensed under the Apache License, Version 2.0. | |
| The backbone (Sources/MLXAnyCalib/DINOv2.swift) is a translation of DINOv2's | |
| vision transformer, vendored into AnyCalib and fine-tuned by its authors. | |
| -------------------------------------------------------------------------------- | |
| Modifications made by this project | |
| * Translated from PyTorch to Swift/MLX. | |
| * Checkpoint weights are converted from PyTorch .pt to safetensors, with | |
| convolution tensors transposed from NCHW to NHWC for MLX's native layout. | |
| No weight values are altered beyond an optional float32 -> float16 cast. | |
| * Deviations from the reference implementation's numerics are enumerated in | |
| the "Deliberate deviations" section of README.md. | |