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Tryoffanyone
Overview :
TryOffAnyone is a deep learning model designed to generate flat fabric images from photos of individuals wearing clothing. This model transforms images of clothed people into fabric flat-lays, which is significant for fashion design and virtual fitting applications. By leveraging deep learning technology, it achieves highly realistic fabric simulations, allowing users to intuitively preview how garments appear when worn. The main advantages of this model include realistic fabric simulation effects and a high degree of automation, which can reduce time and cost in the actual fitting process.
Target Users :
Target audience includes fashion designers, virtual fitting software developers, and researchers in computer vision. TryOffAnyone aids them in quickly previewing clothing designs, reducing the need for physical sample production, while providing technical support for virtual fitting, thus enhancing user experience.
Use Cases
Fashion designers use TryOffAnyone to preview the wearing effects of their new clothing designs.
E-commerce platforms utilize TryOffAnyone to provide online virtual fitting services.
Researchers employ TryOffAnyone for fabric simulation and studies in the field of computer vision.
Features
- Generates flat fabric images from clothed individuals.
- Supports simulation of upper-body clothing, similar to those in the VITON-HD dataset.
- Capable of processing any image URL and outputting simulation results.
- Provides detailed installation and usage guidelines.
- Supports evaluation on the VITON-HD dataset.
- Allows users to download the model and perform inference locally.
- Offers open-source access to the code and pre-trained models.
How to Use
1. Clone the TryOffAnyone code repository to your local machine.
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2. Install the required dependencies.
3. Download the pre-trained model from the provided link and place it in the specified directory.
4. Use the command-line tool provided to input an image URL for fabric simulation.
5. View the output results, usually saved in the designated data directory.
6. If evaluation on the VITON-HD dataset is required, download and extract the dataset, and run the evaluation script.
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