BoxMOT
Pluggable SOTA multi-object tracking modules for segmentation, object detection, and pose estimation models.
Discover and deploy pre-trained AI models for fashion-related tasks.
Hugging Face hosts a wide array of pre-trained AI models applicable to various fashion-related tasks. These models are built using frameworks like PyTorch, TensorFlow, and Transformers, providing capabilities such as object detection (e.g., identifying clothing items), image classification (e.g., categorizing garments), image segmentation (e.g., delineating garment regions), text classification (e.g., classifying fashion articles), and generative modeling (e.g., creating new fashion designs). The platform facilitates collaborative development with Git-based repositories. Users can deploy these models on dedicated infrastructure through Inference Endpoints or leverage services like AWS, Azure, and Google Cloud for scalable deployments. Hugging Face offers tiered pricing, including a free tier and paid plans for enhanced resources and features.
Hugging Face hosts a wide array of pre-trained AI models applicable to various fashion-related tasks.
Explore all tools that specialize in object detection. This domain focus ensures Hugging Face Fashion Models delivers optimized results for this specific requirement.
Explore all tools that specialize in image classification. This domain focus ensures Hugging Face Fashion Models delivers optimized results for this specific requirement.
Explore all tools that specialize in image segmentation. This domain focus ensures Hugging Face Fashion Models delivers optimized results for this specific requirement.
Explore all tools that specialize in text classification. This domain focus ensures Hugging Face Fashion Models delivers optimized results for this specific requirement.
Explore all tools that specialize in text-to-image. This domain focus ensures Hugging Face Fashion Models delivers optimized results for this specific requirement.
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Pluggable SOTA multi-object tracking modules for segmentation, object detection, and pose estimation models.

A simple, fast, and strong multi-object tracker that associates every detection box.

Labeled subsets of the 80 million tiny images dataset for machine learning research.

AI Inference platform offering developer-friendly APIs for performance and cost-efficiency.

A large-scale street fashion dataset with polygon annotations for computer vision research.

A pure ConvNet model constructed entirely from standard ConvNet modules, designed for the 2020s.