add try off

.gitignore

@@ -53,3 +53,6 @@ Thumbs.db
 
 # Gradio cache
 .gradio/example/github.mp4
+
+aws/
+checkpoints/

README.md

@@ -22,6 +22,9 @@ Running it now on website: [CATVTON-FLUX-TRY-ON](https://huggingface.co/spaces/x
 ---
 **Latest Achievement** 
 
+(2024/12/6):
+- Released a new weights for tryoff. The model named [cat-tryoff-flux](https://huggingface.co/xiaozaa/cat-tryoff-flux) can extract and reconstruct the front view of clothing items from images of people wearing them.
+
 (2024/12/1):
 - Community comfyui support [here](https://github.com/lujiazho/ComfyUI-CatvtonFluxWrapper). Thanks to [lujiazho](https://github.com/lujiazho)
 
@@ -43,17 +46,31 @@ Running it now on website: [CATVTON-FLUX-TRY-ON](https://huggingface.co/spaces/x
 ---
 
 ## Showcase
+
+### Try-on examples
 | Original | Garment | Result |
 |----------|---------|---------|
 | ![Original](example/person/1.jpg) | ![Garment](example/garment/00035_00.jpg) | ![Result](example/result/1.png) |
 | ![Original](example/person/1.jpg) | ![Garment](example/garment/04564_00.jpg) | ![Result](example/result/2.png) |
 | ![Original](example/person/00008_00.jpg) | ![Garment](example/garment/00034_00.jpg) | ![Result](example/result/3.png) |
 
+### Try-off examples
+| Original clothed model | Restored garment result |
+|------------------------|------------------------|
+| ![Original](example/person/00055_00.jpg) | ![Restored garment result](example/tryoff_result/restored_garment2.png) |
+| ![Original](example/person/00064_00.jpg) | ![Restored garment result](example/tryoff_result/restored_garment4.png) |
+| ![Original](example/person/00069_00.jpg) | ![Restored garment result](example/tryoff_result/restored_garment6.png) |
+
+
 ## Model Weights
+### Tryon
 Fine-tuning weights in Hugging Face: 🤗 [catvton-flux-alpha](https://huggingface.co/xiaozaa/catvton-flux-alpha)
-
 LORA weights in Hugging Face: 🤗 [catvton-flux-lora-alpha](https://huggingface.co/xiaozaa/catvton-flux-lora-alpha)
 
+### Tryoff
+Fine-tuning weights in Hugging Face: 🤗 [cat-tryoff-flux](https://huggingface.co/xiaozaa/cat-tryoff-flux)
+
+### Dataset
 The model weights are trained on the [VITON-HD](https://github.com/shadow2496/VITON-HD) dataset.
 
 ## Prerequisites
@@ -69,6 +86,19 @@ huggingface-cli login
 
 ## Usage
 
+### Tryoff
+Run the following command to restore the front side of the garment from the clothed model image:
+```bash
+python tryoff_inference.py \
+--image ./example/person/00069_00.jpg \
+--mask ./example/person/00069_00_mask.png \
+--seed 41 \
+--output_tryon test_original.png \
+--output_garment restored_garment6.png \
+--steps 30
+```
+
+### Tryon
 Run the following command to try on an image:
 
 LORA version:
@@ -104,7 +134,7 @@ python app_no_lora.py
 ```
 
 Gradio demo:
-
+Hugging Face: 🤗 [CATVTON-FLUX-TRY-ON](https://huggingface.co/spaces/xiaozaa/catvton-flux-try-on)
 <!-- Option 2: Using a thumbnail linked to the video -->
 [![Demo](example/github.jpg)](https://upcdn.io/FW25b7k/raw/uploads/github.mp4)
 
@@ -114,8 +144,8 @@ Gradio demo:
 - [x] Add gradio demo
 - [x] Release updated weights with better performance
 - [x] Train a smaller model
-- [ ] Support comfyui
-
+- [x] Support comfyui
+- [x] Release tryoff weights
 ## Citation
 
 ```bibtex

requirements.txt

@@ -11,3 +11,4 @@ sentencepiece
 peft==0.13.2
 huggingface-hub
 spaces
+protobuf

tryoff.sh

@@ -0,0 +1,7 @@
+python tryoff_inference.py \
+--image ./example/person/00069_00.jpg \
+--mask ./example/person/00069_00_mask.png \
+--seed 41 \
+--output_tryon test_original.png \
+--output_garment restored_garment6.png \
+--steps 30

tryoff_inference.py

@@ -0,0 +1,117 @@
+import argparse
+import torch
+from diffusers.utils import load_image, check_min_version
+from diffusers import FluxPriorReduxPipeline, FluxFillPipeline
+from diffusers import FluxTransformer2DModel
+import numpy as np
+from torchvision import transforms
+
+def run_inference(
+    image_path,
+    mask_path,
+    size=(576, 768),
+    num_steps=50,
+    guidance_scale=30,
+    seed=42,
+    pipe=None
+):
+    # Build pipeline
+    if pipe is None:
+        transformer = FluxTransformer2DModel.from_pretrained(
+            "xiaozaa/cat-tryoff-flux", 
+            torch_dtype=torch.bfloat16
+        )
+        pipe = FluxFillPipeline.from_pretrained(
+            "black-forest-labs/FLUX.1-dev",
+            transformer=transformer,
+            torch_dtype=torch.bfloat16
+        ).to("cuda")
+    else:
+        pipe.to("cuda")
+
+    pipe.transformer.to(torch.bfloat16)
+
+    # Add transform
+    transform = transforms.Compose([
+        transforms.ToTensor(),
+        transforms.Normalize([0.5], [0.5])  # For RGB images
+    ])
+    mask_transform = transforms.Compose([
+        transforms.ToTensor()
+    ])
+
+    # Load and process images
+    # print("image_path", image_path)
+    image = load_image(image_path).convert("RGB").resize(size)
+    mask = load_image(mask_path).convert("RGB").resize(size)
+
+    # Transform images using the new preprocessing
+    image_tensor = transform(image)
+    mask_tensor = mask_transform(mask)[:1]  # Take only first channel
+    garment_tensor = torch.zeros_like(image_tensor)
+    image_tensor = image_tensor * mask_tensor
+
+    # Create concatenated images
+    inpaint_image = torch.cat([garment_tensor, image_tensor], dim=2)  # Concatenate along width
+    garment_mask = torch.zeros_like(mask_tensor)
+    extended_mask = torch.cat([1 - garment_mask, garment_mask], dim=2)
+
+    prompt = f"The pair of images highlights a clothing and its styling on a model, high resolution, 4K, 8K; " \
+            f"[IMAGE1] Detailed product shot of a clothing" \
+            f"[IMAGE2] The same cloth is worn by a model in a lifestyle setting."
+
+    generator = torch.Generator(device="cuda").manual_seed(seed)
+
+    result = pipe(
+        height=size[1],
+        width=size[0] * 2,
+        image=inpaint_image,
+        mask_image=extended_mask,
+        num_inference_steps=num_steps,
+        generator=generator,
+        max_sequence_length=512,
+        guidance_scale=guidance_scale,
+        prompt=prompt,
+    ).images[0]
+
+    # Split and save results
+    width = size[0]
+    garment_result = result.crop((0, 0, width, size[1]))
+    tryon_result = result.crop((width, 0, width * 2, size[1]))
+    
+    return garment_result, tryon_result
+
+def main():
+    parser = argparse.ArgumentParser(description='Run FLUX virtual try-on inference')
+    parser.add_argument('--image', required=True, help='Path to the model image')
+    parser.add_argument('--mask', required=True, help='Path to the agnostic mask')
+    parser.add_argument('--output_garment', default='flux_inpaint_garment.png', help='Output path for garment result')
+    parser.add_argument('--output_tryon', default='flux_inpaint_tryon.png', help='Output path for try-on result')
+    parser.add_argument('--steps', type=int, default=50, help='Number of inference steps')
+    parser.add_argument('--guidance_scale', type=float, default=30, help='Guidance scale')
+    parser.add_argument('--seed', type=int, default=0, help='Random seed')
+    parser.add_argument('--width', type=int, default=576, help='Width')
+    parser.add_argument('--height', type=int, default=768, help='Height')
+    
+    args = parser.parse_args()
+    
+    check_min_version("0.30.2")
+    
+    garment_result, tryon_result = run_inference(
+        image_path=args.image,
+        mask_path=args.mask,
+        num_steps=args.steps,
+        guidance_scale=args.guidance_scale,
+        seed=args.seed,
+        size=(args.width, args.height)
+    )
+    output_tryon_path=args.output_tryon
+    output_garment_path=args.output_garment
+    
+    tryon_result.save(output_tryon_path)
+    garment_result.save(output_garment_path)
+    
+    print("Successfully saved garment and try-on images")
+
+if __name__ == "__main__":
+    main()

tryon.sh

@@ -0,0 +1,7 @@
+python tryon_inference.py \
+--image ./example/person/00008_00.jpg \
+--mask ./example/person/00008_00_mask.png \
+--garment ./example/garment/00034_00.jpg \
+--seed 42 \
+--output_tryon test.png \
+--steps 30