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Open-source toolbox for visual fashion analysis based on PyTorch.

MMFashion is an open-source visual fashion analysis toolbox built on PyTorch, designed for researchers and developers in the field of fashion AI. It supports a wide range of tasks, including fashion attribute prediction, recognition and retrieval, landmark detection, parsing and segmentation, compatibility and recommendation, and virtual try-on. Its modular design allows for flexible customization and extension. The toolbox includes pre-trained models for ease of use and provides comprehensive documentation for getting started, data preparation, and contributing. MMFashion uses Python 3.5+, PyTorch 1.0.0+, and mmcv, and can be installed via git clone and setup.py or using a Docker image. It offers tools for fashion detection, fashion landmarks, and fashion cut analysis, making it a valuable resource for developing AI-powered fashion applications.
MMFashion is an open-source visual fashion analysis toolbox built on PyTorch, designed for researchers and developers in the field of fashion AI.
Explore all tools that specialize in fashion landmark detection. This domain focus ensures MMFashion delivers optimized results for this specific requirement.
The toolbox is designed with a modular architecture, allowing users to easily extend and customize the components for specific tasks.
MMFashion provides off-the-shelf pre-trained models for various fashion analysis tasks, reducing the need for extensive training from scratch.
The toolbox supports a wide spectrum of fashion analysis tasks, including attribute prediction, recognition, landmark detection, parsing, compatibility, recommendation, and virtual try-on.
MMFashion includes a dedicated module for fashion segmentation and parsing, enabling fine-grained analysis of clothing items.
The toolbox features a virtual try-on module, allowing users to simulate how clothing items would look on a person.
1. Install Python 3.5+ and PyTorch 1.0.0+.
2. Install mmcv.
3. Clone the MMFashion repository using 'git clone --recursive https://github.com/open-mmlab/mmfashion.git'.
4. Navigate to the MMFashion directory using 'cd mmfashion'.
5. Install the toolbox using 'python setup.py install'.
6. Alternatively, build a Docker image using the provided Dockerfile.
7. Refer to GETTING_STARTED.md for basic usage instructions.
All Set
Ready to go
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