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[CVPR 2024] Depth Anything: Unleashing the Power of Large-Scale Unlabeled Data. Foundation Model for Monocular Depth Estimation

Efficient vision foundation models for high-resolution generation and perception.

PyTorch native quantization and sparsity for training and inference

A PyTorch Library for Multi-Task Learning

A (PyTorch) imbalanced dataset sampler for oversampling low frequent classes and undersampling high frequent ones.

HDF5 for Python -- The h5py package is a Pythonic interface to the HDF5 binary data format.

A simple way to calibrate your neural network.

A distilled Segment Anything (SAM) model capable of running real-time with NVIDIA TensorRT

A framework for Smoothed Particle Hydrodynamics in Python