osmr/imgclsmob

Health v2 · maintenance only

Adoption not part of the score

3016 stars · 551 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A research sandbox providing (re)implementations of numerous deep learning computer vision models for classification, segmentation, detection, and pose estimation across six frameworks (MXNet/Gluon, PyTorch, Chainer, Keras, TensorFlow 1.x/2.x). It includes training/evaluation/conversion scripts and automatically loadable pretrained weights distributed via per-framework PyPI packages like pytorchcv.

Use cases

• find pretrained image classification models for pytorch
• train a model on imagenet or cifar
• get the same model implemented in multiple frameworks
• semantic segmentation models with pretrained weights
• human pose estimation model implementations
• convert models between deep learning frameworks
• benchmark cnn architectures on imagenet

When to choose

• you need a wide zoo of CNN architectures with pretrained weights in PyTorch, TensorFlow, Keras, Gluon, Chainer, or TF2
• you want consistent cross-framework implementations of the same model
• you need training and evaluation scripts for ImageNet, CIFAR, Pascal VOC, ADE20K, Cityscapes, or COCO

When to avoid

• you need transformer-based or latest SOTA vision models only
• you want a high-level production inference API rather than model definitions
• you work outside the six supported frameworks

Facets

library · maturity active

deep-learning machine-learning image-processing computer-vision deep-learning computer-vision machine-learning image-processing python cross-platform pretrained-models image-classification semantic-segmentation pose-estimation pytorch tensorflow mxnet keras chainer model-zoo imagenet

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