Update app.py

app.py

@@ -1,3 +1,83 @@
-import os
+import spaces
+from diffusers import AutoPipelineForInpainting, AutoencoderKL
+import gradio as gr
+from diffusers.utils import load_image
+import torch
+from PIL import Image
+from SegBody import segment_body
+from SegCloth import segment_clothing
 
-exec(os.environ.get('APP'))
+vae = AutoencoderKL.from_pretrained("madebyollin/sdxl-vae-fp16-fix", torch_dtype=torch.float16)
+pipeline = AutoPipelineForInpainting.from_pretrained(os.environ.get('MODEL'), vae=vae, torch_dtype=torch.float16, variant="fp16", use_safetensors=True).to("cuda")
+pipeline.load_ip_adapter(os.environ.get('IP_ADAPTER'), subfolder="sdxl_models", weight_name="ip-adapter_sdxl.bin")
+
+@spaces.GPU(enable_queue=True)
+def squarify_image(img):
+    if(img.height > img.width): bg_size = img.height
+    else:  bg_size = img.width
+    bg = Image.new(mode="RGB", size=(bg_size,bg_size), color="white")
+    bg.paste(img, ( int((bg.width - bg.width)/2), 0) )
+
+    return bg
+
+@spaces.GPU(enable_queue=True)
+def divisible_by_8(image):
+    width, height = image.size
+    
+    # Calculate the new width and height that are divisible by 8
+    new_width = (width // 8) * 8
+    new_height = (height // 8) * 8
+    
+    # Resize the image
+    resized_image = image.resize((new_width, new_height))
+    
+    return resized_image
+
+@spaces.GPU(enable_queue=True)
+def generate(person, clothing):
+    person.thumbnail((1024,1024))
+    person = divisible_by_8(person)
+    
+    clothing.thumbnail((1024,1024))
+    clothing = divisible_by_8(clothing)
+
+    image = squarify_image(person)
+
+    seg_image, mask_image = segment_body(image, face=False)
+
+    seg_cloth = segment_clothing(clothing, clothes= ["Upper-clothes", "Skirt", "Pants", "Dress", "Belt"])
+    #seg_cloth = clothing
+    
+    pipeline.to("cuda")
+    pipeline.set_ip_adapter_scale(1.0)
+    images = pipeline(
+        prompt="photorealistic, perfect body, beautiful skin, realistic skin, natural skin",
+        negative_prompt="ugly, bad quality, bad anatomy, deformed body, deformed hands, deformed feet, deformed face, deformed clothing, deformed skin, bad skin, leggings, tights, stockings",
+        image=image,
+        mask_image=mask_image,
+        ip_adapter_image=seg_cloth,
+        width=image.width,
+        height=image.height,
+        strength=0.99,
+        guidance_scale=7.5,
+        num_inference_steps=100,
+    ).images
+    
+    final = images[0].crop((0, 0, person.width, person.height))
+    
+    return final
+
+iface = gr.Interface(fn=generate, 
+                     inputs=[gr.Image(label='Person', type='pil'), gr.Image(label='Clothing', type='pil')], 
+                     outputs=[gr.Image(label='Result')],
+                     title='Fashion Try-On',
+                     description="""
+                     by [Tony Assi](https://www.tonyassi.com/)
+
+                     Check out [Virtual Try-On Pro](https://huggingface.co/spaces/tonyassi/Virtual-Try-On-Pro) !
+                     
+                     Please ❤️ this Space. I build custom AI apps for companies. <a href="mailto: tony.assi.media@gmail.com">Email me</a> for business inquiries.
+                     """,
+                     theme = gr.themes.Base(primary_hue="teal",secondary_hue="teal",neutral_hue="slate"),
+                     examples=[["images/person1.jpg", "images/clothing1.jpg"], ["images/person1.jpg", "images/clothing2.jpg"]],)
+iface.launch()