modelle_diffuser Virtual Try-On:

Input:

• Person's image.

• Clothing item.

Modules:

• Person Detection + Segmentation:

  • Mask R-CNN

• Pose Estimation:

  • estimation models

• Clothing Warp and Alignment: warping clothing item according to the pose of the person.

  • Thin Plate Spline (TPS): used for warping

• Blending and Rendering: seamlessly blend the warped clothing onto the person.

  • GANs: used for realistic rendering

Implementation Strategy:

• Multiple U-Nets for Simultaneous Processing:

  • One U-Net for person detection and segmentation.

  • Another U-Net for pose estimation.

  • Additional U-Nets for clothing warping, which will work in tandem to adjust for different aspects like size, orientation, and position.

• Integration of Stable Diffusion: Integrate stable diffusion models for realistic texturing and blending of the clothing with the person’s image.

• Post-Processing: To ensure the quality of the final image, post-processing steps might be required to refine edges, adjust colors, and enhance realism.