apple/ml-cvnets

Health v2 · maintenance only

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1983 stars · 258 forks observed · 2026-08-28

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

CVNets is Apple's open-source PyTorch library for training computer vision networks, covering classification, detection, segmentation, video classification, and foundation models like CLIP. It includes implementations of many state-of-the-art mobile and non-mobile architectures (MobileNet, EfficientNet, ViT, MobileViT, Swin) plus data loading, augmentation, and sampling tools.

Use cases

• train an image classification model on ImageNet
• train object detection models on MS-COCO
• train semantic segmentation models like DeepLabv3
• train CLIP-style foundation models
• train mobile-friendly vision transformers like MobileViT
• convert trained PyTorch vision models to CoreML
• train video classification models on Kinetics

When to choose

• you need to train or reproduce vision models from Apple's research papers (MobileViT, RangeAugment, etc.)
• you want a single PyTorch toolkit spanning classification, detection, and segmentation
• you target mobile deployment and need efficient vision architectures with CoreML export

When to avoid

• you only need pretrained models for inference rather than training
• you prefer higher-level frameworks like torchvision, timm, or MMDetection with larger communities
• you need active development or timely updates, as the project has not seen recent releases

Facets

library · maturity maintenance

machine-learning deep-learning image-processing computer-vision computer-vision deep-learning machine-learning image-processing python cross-platform pytorch image-classification object-detection semantic-segmentation clip model-training mobile-vision-models coreml imagenet mscoco gpu

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