Update app.py

app.py

@@ -19,7 +19,7 @@ hf_hub_download(
     repo_id="black-forest-labs/FLUX.1-Redux-dev", 
     filename="flux1-redux-dev.safetensors", 
     local_dir="models/style_models",
-    token=HF_TOKEN  # 토큰 전달
+    token=HF_TOKEN
 )
 hf_hub_download(
     repo_id="black-forest-labs/FLUX.1-Depth-dev", 
@@ -27,23 +27,43 @@ hf_hub_download(
     local_dir="models/diffusion_models",
     token=HF_TOKEN
 )
-# 나머지 hf_hub_download 호출에도 token=HF_TOKEN 추가
-hf_hub_download(repo_id="Comfy-Org/sigclip_vision_384", filename="sigclip_vision_patch14_384.safetensors", local_dir="models/clip_vision", token=HF_TOKEN)
-hf_hub_download(repo_id="Kijai/DepthAnythingV2-safetensors", filename="depth_anything_v2_vitl_fp32.safetensors", local_dir="models/depthanything", token=HF_TOKEN)
-hf_hub_download(repo_id="black-forest-labs/FLUX.1-dev", filename="ae.safetensors", local_dir="models/vae/FLUX1", token=HF_TOKEN)
-hf_hub_download(repo_id="comfyanonymous/flux_text_encoders", filename="clip_l.safetensors", local_dir="models/text_encoders", token=HF_TOKEN)
-t5_path = hf_hub_download(repo_id="comfyanonymous/flux_text_encoders", filename="t5xxl_fp16.safetensors", local_dir="models/text_encoders/t5", token=HF_TOKEN)
-
-
+hf_hub_download(
+    repo_id="Comfy-Org/sigclip_vision_384", 
+    filename="sigclip_vision_patch14_384.safetensors", 
+    local_dir="models/clip_vision",
+    token=HF_TOKEN
+)
+hf_hub_download(
+    repo_id="Kijai/DepthAnythingV2-safetensors", 
+    filename="depth_anything_v2_vitl_fp32.safetensors", 
+    local_dir="models/depthanything",
+    token=HF_TOKEN
+)
+hf_hub_download(
+    repo_id="black-forest-labs/FLUX.1-dev", 
+    filename="ae.safetensors", 
+    local_dir="models/vae/FLUX1",
+    token=HF_TOKEN
+)
+hf_hub_download(
+    repo_id="comfyanonymous/flux_text_encoders", 
+    filename="clip_l.safetensors", 
+    local_dir="models/text_encoders",
+    token=HF_TOKEN
+)
+t5_path = hf_hub_download(
+    repo_id="comfyanonymous/flux_text_encoders", 
+    filename="t5xxl_fp16.safetensors", 
+    local_dir="models/text_encoders/t5",
+    token=HF_TOKEN
+)
 
-# Import all the necessary functions from the original script
 def get_value_at_index(obj: Union[Sequence, Mapping], index: int) -> Any:
     try:
         return obj[index]
     except KeyError:
         return obj["result"][index]
 
-# Add all the necessary setup functions from the original script
 def find_path(name: str, path: str = None) -> str:
     if path is None:
         path = os.getcwd()
@@ -77,6 +97,8 @@ def add_extra_model_paths() -> None:
 add_comfyui_directory_to_sys_path()
 add_extra_model_paths()
 
+
+
 def import_custom_nodes() -> None:
     import asyncio
     import execution
@@ -109,8 +131,6 @@ from nodes import (
 import_custom_nodes()
 
 # Global variables for preloaded models and constants
-#with torch.inference_mode():
-    # Initialize constants
 intconstant = NODE_CLASS_MAPPINGS["INTConstant"]()
 CONST_1024 = intconstant.get_value(value=1024)
 
@@ -154,6 +174,8 @@ downloadandloaddepthanythingv2model = NODE_CLASS_MAPPINGS["DownloadAndLoadDepthA
 DEPTH_MODEL = downloadandloaddepthanythingv2model.loadmodel(
     model="depth_anything_v2_vitl_fp32.safetensors"
 )
+
+# Initialize other nodes
 cliptextencode = CLIPTextEncode()
 loadimage = LoadImage()
 vaeencode = VAEEncode()
@@ -297,7 +319,7 @@ def generate_image(prompt, structure_image, style_image, depth_strength=15, styl
         )
         
         # Save image
-        prefix = cr_text.text_multiline(text="Flux_BFL_Depth_Redux")
+        prefix = cr_text.text_multiline(text="Virtual_TryOn")
         
         saved = saveimage.save_images(
             filename_prefix=get_value_at_index(prefix, 0),
@@ -307,29 +329,50 @@ def generate_image(prompt, structure_image, style_image, depth_strength=15, styl
         return saved_path
 
 # Create Gradio interface
-
 examples = [
-    ["", "mona.png", "receita-tacos.webp", 15, 0.6],
-    ["a woman looking at a house catching fire on the background", "disaster_girl.png", "abaporu.jpg", 15, 0.15],
-    ["istanbul aerial, dramatic photography", "natasha.png", "istambul.jpg", 15, 0.5],
+    ["person wearing fashionable clothing", "person.jpg", "fashion1.jpg", 15, 0.6],
+    ["person wearing elegant dress", "model1.jpg", "dress1.jpg", 15, 0.5],
+    ["person wearing casual outfit", "person2.jpg", "outfit1.jpg", 15, 0.5],
 ]
 
-output_image = gr.Image(label="Generated Image")
+output_image = gr.Image(label="Virtual Try-On Result")
 
 with gr.Blocks() as app:
-    gr.Markdown("# FLUX Style Shaping")
-    gr.Markdown("Flux[dev] Redux + Flux[dev] Depth ComfyUI workflow by [Nathan Shipley](https://x.com/CitizenPlain) running directly on Gradio. [workflow](https://gist.github.com/nathanshipley/7a9ac1901adde76feebe58d558026f68) - [how to convert your any comfy workflow to gradio (soon)](#)")
+    gr.Markdown("# AI Fashion Virtual Try-On")
+    gr.Markdown("Upload your photo and try on different clothing items virtually using AI. The system will generate an image of you wearing the selected clothing while maintaining your pose and appearance.")
+    
     with gr.Row():
         with gr.Column():
-            prompt_input = gr.Textbox(label="Prompt", placeholder="Enter your prompt here...")
+            prompt_input = gr.Textbox(
+                label="Style Description", 
+                placeholder="Describe the desired style (e.g., 'person wearing elegant dress')"
+            )
             with gr.Row():
                 with gr.Group():
-                    structure_image = gr.Image(label="Structure Image", type="filepath")
-                    depth_strength = gr.Slider(minimum=0, maximum=50, value=15, label="Depth Strength")
+                    structure_image = gr.Image(
+                        label="Your Photo", 
+                        type="filepath",
+                        info="Upload a full-body photo of yourself"
+                    )
+                    depth_strength = gr.Slider(
+                        minimum=0, 
+                        maximum=50, 
+                        value=15, 
+                        label="Fitting Strength"
+                    )
                 with gr.Group():
-                    style_image = gr.Image(label="Style Image", type="filepath")
-                    style_strength = gr.Slider(minimum=0, maximum=1, value=0.5, label="Style Strength")
-            generate_btn = gr.Button("Generate")
+                    style_image = gr.Image(
+                        label="Clothing Item", 
+                        type="filepath",
+                        info="Upload the clothing item you want to try on"
+                    )
+                    style_strength = gr.Slider(
+                        minimum=0, 
+                        maximum=1, 
+                        value=0.5, 
+                        label="Style Transfer Strength"
+                    )
+            generate_btn = gr.Button("Generate Try-On")
             
             gr.Examples(
                 examples=examples,
@@ -342,6 +385,22 @@ with gr.Blocks() as app:
         
         with gr.Column():
             output_image.render()
+    
+    gr.Markdown("""
+    ### How to Use:
+    1. Upload your full-body photo
+    2. Upload the clothing item you want to try on
+    3. Adjust the fitting and style strength if needed
+    4. Add a description of the desired style (optional)
+    5. Click 'Generate Try-On' to see the result
+    
+    ### Tips:
+    - Use clear, well-lit photos
+    - Full-body photos work best
+    - Clothing items should be on a clean background
+    - Adjust the fitting strength for better results
+    """)
+    
     generate_btn.click(
         fn=generate_image,
         inputs=[prompt_input, structure_image, style_image, depth_strength, style_strength],