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Merge pull request #19 from nftblackmagic/anzh/tryoff
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Anzh/tryoff
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nftblackmagic authored Dec 6, 2024
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# Gradio cache
.gradio/example/github.mp4

aws/
checkpoints/
37 changes: 34 additions & 3 deletions README.md
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Expand Up @@ -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. [Showcase examples](#try-off-examples) is here.

(2024/12/1):
- Community comfyui support [here](https://github.com/lujiazho/ComfyUI-CatvtonFluxWrapper). Thanks to [lujiazho](https://github.com/lujiazho)

Expand All @@ -43,17 +46,32 @@ 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
Expand All @@ -69,6 +87,19 @@ 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:
Expand Down Expand Up @@ -104,7 +135,7 @@ 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)

Expand All @@ -114,8 +145,8 @@ 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
Expand Down
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1 change: 1 addition & 0 deletions requirements.txt
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peft==0.13.2
huggingface-hub
spaces
protobuf
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7 changes: 7 additions & 0 deletions tryoff.sh
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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
117 changes: 117 additions & 0 deletions tryoff_inference.py
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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()
7 changes: 7 additions & 0 deletions tryon.sh
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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

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