added more changes

README.md

@@ -1,5 +1,5 @@
 ---
-title: Garment3dKabeer
+title: Garment3d
 emoji: 📊
 colorFrom: yellow
 colorTo: gray

app.py

@@ -126,16 +126,18 @@ DEFAULT_CONFIG = {
     'log_light_power': 3.0
 }
 
-def process_garment(input_type, text_prompt, base_text_prompt, target_image, base_image, custom_mesh, epochs, learning_rate, clip_weight, delta_clip_weight, progress=gr.Progress()):
+def process_garment(input_type, text_prompt, base_text_prompt, target_image, base_image, mesh_target_image, source_mesh_type, custom_mesh, epochs, learning_rate, clip_weight, delta_clip_weight, progress=gr.Progress()):
     """
     Main function to process garment generation
     
     Args:
-        input_type: Either "Text" or "Image" to determine the processing mode
+        input_type: Either "Text", "Image", or "Image to Mesh" to determine the processing mode
         text_prompt: Text description of target garment (for text mode)
         base_text_prompt: Text description of base garment (for text mode)
         target_image: Image of target garment style (for image mode)
         base_image: Optional image of base garment (for image mode)
+        mesh_target_image: Image for generating a 3D mesh (for image to mesh mode)
+        source_mesh_type: Type of source mesh to use as starting point (for image to mesh mode)
         custom_mesh: Optional custom source mesh file (.obj)
         epochs: Number of optimization epochs
         learning_rate: Optimization learning rate
@@ -150,7 +152,40 @@ def process_garment(input_type, text_prompt, base_text_prompt, target_image, bas
             config = DEFAULT_CONFIG.copy()
             
             # Set up input parameters based on mode
-            if input_type == "Image" and target_image is not None:
+            if input_type == "Image to Mesh" and mesh_target_image is not None:
+                # Image-to-Mesh processing
+                progress(0.05, desc="Preparing mesh generation from image...")
+                
+                # Save target image to temp directory
+                target_mesh_image_path = os.path.join(temp_dir, "target_mesh_image.jpg")
+                
+                if isinstance(mesh_target_image, str):
+                    shutil.copy(mesh_target_image, target_mesh_image_path)
+                elif isinstance(mesh_target_image, np.ndarray):
+                    img = Image.fromarray(mesh_target_image.astype(np.uint8))
+                    img.save(target_mesh_image_path)
+                elif hasattr(mesh_target_image, 'save'):
+                    mesh_target_image.save(target_mesh_image_path)
+                else:
+                    print(f"Unsupported image type: {type(mesh_target_image)}")
+                    return None
+                
+                print(f"Target mesh image saved to {target_mesh_image_path}")
+                
+                # Set mesh paths based on selected source mesh type
+                source_mesh_file = f"./meshes/{source_mesh_type}.obj"
+                
+                # Configure for image-to-mesh processing
+                config.update({
+                    'mesh': source_mesh_file,
+                    'image_prompt': target_mesh_image_path,
+                    'base_image_prompt': target_mesh_image_path,  # Use same image as base
+                    'use_target_mesh': True,
+                    'fashion_image': True,
+                    'fashion_text': False,
+                })
+                
+            elif input_type == "Image" and target_image is not None:
                 # Image-based processing
                 progress(0.05, desc="Preparing image inputs...")
                 
@@ -348,17 +383,18 @@ def create_interface():
         that can be used for virtual try-on applications.
         
         ## How to use:
-        1. Choose either **Text** or **Image** input mode using the radio button below
+        1. Choose **Text**, **Image**, or **Image to Mesh** input mode using the radio button below
         2. For **Text** mode: Enter descriptions of your target and base garment styles
         3. For **Image** mode: Upload an image of your desired garment style
-        4. Click "Generate 3D Garment" to create your 3D mesh file
+        4. For **Image to Mesh** mode: Upload an image to generate a 3D mesh directly
+        5. Click "Generate 3D Garment" to create your 3D mesh file
         """)
         
         with gr.Row():
             with gr.Column():
                 # Input type selector
                 input_type = gr.Radio(
-                    choices=["Text", "Image"],
+                    choices=["Text", "Image", "Image to Mesh"],
                     value="Text",
                     label="Generation Method"
                 )
@@ -395,6 +431,24 @@ def create_interface():
                     )
                     gr.Markdown("*Upload a base garment image (optional)*")
                 
+                # Image to Mesh inputs (hidden by default)
+                with gr.Group(visible=False) as image_to_mesh_group:
+                    mesh_target_image = gr.Image(
+                        label="Target Garment Image for Mesh Generation",
+                        sources=["upload", "webcam"],
+                        type="numpy",
+                        interactive=True
+                    )
+                    gr.Markdown("*Upload an image of the garment to convert directly to a 3D mesh*")
+                    
+                    source_mesh_type = gr.Dropdown(
+                        label="Source Mesh Type",
+                        choices=["t-shirt", "longsleeve", "tanktop", "poncho", "dress_shortsleeve"],
+                        value="t-shirt",
+                        interactive=True
+                    )
+                    gr.Markdown("*Select the type of base garment mesh to use as a starting point*")
+                
                 # Custom mesh
                 custom_mesh = gr.File(
                     label="Custom Source Mesh (Optional)",
@@ -448,6 +502,7 @@ def create_interface():
                 
                 - For text mode: Be specific in your descriptions
                 - For image mode: Use clear, front-facing garment images
+                - For image to mesh mode: Use clear garment images to generate a 3D mesh directly
                 - Higher epochs = better quality but longer processing time
                 - Output files can be downloaded by clicking on them
                 
@@ -461,16 +516,20 @@ def create_interface():
         def update_mode(mode):
             text_visibility = mode == "Text"
             image_visibility = mode == "Image"
+            image_to_mesh_visibility = mode == "Image to Mesh"
             status_msg = f"Mode changed to {mode}. "
             
             if text_visibility:
                 status_msg += "Enter garment descriptions and click Generate."
-            else:
+            elif image_visibility:
                 status_msg += "Upload garment images and click Generate."
+            else:
+                status_msg += "Upload a garment image and select mesh type, then click Generate."
                 
             return (
                 gr.Group.update(visible=text_visibility),
                 gr.Group.update(visible=image_visibility),
+                gr.Group.update(visible=image_to_mesh_visibility),
                 status_msg
             )
             
@@ -491,7 +550,7 @@ def create_interface():
         input_type.change(
             fn=update_mode,
             inputs=[input_type],
-            outputs=[text_group, image_group, status_output]
+            outputs=[text_group, image_group, image_to_mesh_group, status_output]
         )
         
         # Connect the button to the processing function with error handling
@@ -503,6 +562,8 @@ def create_interface():
                 base_text_prompt,
                 target_image,
                 base_image,
+                mesh_target_image,
+                source_mesh_type,
                 custom_mesh,
                 epochs,
                 learning_rate,