Update app.py

app.py

@@ -13,7 +13,6 @@ import subprocess
 import shutil
 import base64
 import logging
-import requests  # Added for download_image
 
 # Set up logging
 logging.basicConfig(level=logging.INFO, format='%(asctime)s - %(levelname)s - %(message)s')
@@ -292,6 +291,7 @@ def get_random_seed(randomize_seed, seed):
         logger.error(f"Error in get_random_seed: {str(e)}")
         raise
 
+
 def download_image(url: str, save_path: str) -> str:
     """Download an image from a URL and save it locally."""
     try:
@@ -340,7 +340,7 @@ def run_segmentation(image):
 @spaces.GPU(duration=5)
 @torch.no_grad()
 def image_to_3d(
-    image,
+    image,  # Changed to accept FileData dict or PIL Image
     seed: int,
     num_inference_steps: int,
     guidance_scale: float,
@@ -485,7 +485,7 @@ def run_texture(image: Image, mesh_path: str, seed: int, req: gr.Request):
         logger.error(f"Error in run_texture: {str(e)}")
         raise
 
-@spaces.GPU(duration=10)
+@spaces.GPU(duration=5)
 @torch.no_grad()
 def run_full_api(image, seed: int = 0, num_inference_steps: int = 50, guidance_scale: float = 7.5, simplify: bool = True, target_face_num: int = DEFAULT_FACE_NUMBER, req: gr.Request = None):
     try:
@@ -509,8 +509,9 @@ def run_full_api(image, seed: int = 0, num_inference_steps: int = 50, guidance_s
                 raise ValueError(f"Invalid image path: {image_path}")
 
         image_seg, mesh_path, textured_glb_path = run_full(image_path, seed, num_inference_steps, guidance_scale, simplify, target_face_num, req)
-        logger.info(f"Generated textured model at /files/{os.path.basename(os.path.dirname(textured_glb_path))}/{os.path.basename(textured_glb_path)}")
-        return image_seg, mesh_path, textured_glb_path  # Return tuple instead of dictionary
+        session_hash = os.path.basename(os.path.dirname(textured_glb_path))
+        logger.info(f"Generated textured model at /files/{session_hash}/{os.path.basename(textured_glb_path)}")
+        return {"file_url": f"/files/{session_hash}/{os.path.basename(textured_glb_path)}"}
     except Exception as e:
         logger.error(f"Error in run_full_api: {str(e)}")
         raise
@@ -543,8 +544,9 @@ HEADER = """
 ## 🚀 Launch Your Creation:
 1. **Upload an Image** (clear, single-object images shine brightest)
 2. **Choose a Style Filter** to infuse your unique vision
-3. Click **Generate 3D Model** to sculpt your mesh and apply texture
-4. **Download GLB** to share your masterpiece
+3. Click **Generate 3D Model** to sculpt your mesh
+4. Click **Apply Texture** to bring your model to life
+5. **Download GLB** to share your masterpiece
 <p style="font-size: 0.9em; margin-top: 10px; color: #D1D5DB;">Powered by cutting-edge AI and multi-view technology from AnvilInteractive Solutions. Join our <a href="https://www.anvilinteractive.com/community" style="color: #A78BFA; text-decoration: none;">PolyGenixAI Community</a> to connect with creators and spark inspiration.</p>
 <style>
   @import url('https://fonts.googleapis.com/css2?family=Inter:wght@400;600;700&display=swap');
@@ -693,21 +695,25 @@ try:
                 )
                 gr.Markdown("Connect with creators in our <a href='https://www.anvilinteractive.com/community' style='color: #A78BFA; text-decoration: none;'>PolyGenixAI Cosmic Community</a>!")
         gen_button.click(
+            run_segmentation,
+            inputs=[image_prompts],
+            outputs=[seg_image]
+        ).then(
             get_random_seed,
             inputs=[randomize_seed, seed],
             outputs=[seed],
         ).then(
-            run_full_api,
+            image_to_3d,
             inputs=[
-                image_prompts,
+                seg_image,
                 seed,
                 num_inference_steps,
                 guidance_scale,
                 reduce_face,
                 target_face_num
             ],
-            outputs=[seg_image, model_output, textured_model_output]
-        ).then(lambda: gr.Button(interactive=False), outputs=[gen_texture_button])
+            outputs=[model_output]
+        ).then(lambda: gr.Button(interactive=True), outputs=[gen_texture_button])
         gen_texture_button.click(
             run_texture,
             inputs=[image_prompts, model_output, seed],