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import torch
from transformers import AutoModelForCausalLM, AutoTokenizer
from diffusers import StableDiffusionPipeline
import gradio as gr
# Load the model and pipeline
model_id = "ares1123/virtual-dress-try-on"
pipeline = StableDiffusionPipeline.from_pretrained(model_id)
pipeline.to("cuda" if torch.cuda.is_available() else "cpu")
def virtual_try_on(image, clothing_image):
# Process the images using the model
try_on_image = pipeline(image, clothing_image).images[0]
return try_on_image
# Set up a simple Gradio interface for testing
interface = gr.Interface(
fn=virtual_try_on,
inputs=[gr.inputs.Image(type="pil", label="User Image"),
gr.inputs.Image(type="pil", label="Clothing Image")],
outputs="image",
title="Virtual Dress Try-On",
description="Upload an image of yourself and a clothing image to try it on virtually!"
)
# Launch the interface
interface.launch(share=True)
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