Update app.py

app.py

@@ -5,6 +5,7 @@ import torch
 import gradio as gr
 from PIL import Image
 import gc
+import traceback
 from huggingface_hub import snapshot_download
 
 # Add CatVTON to path
@@ -36,7 +37,6 @@ def load_models():
         
         print(f"✅ Models downloaded to: {repo_path}")
         
-        # Create NSFW placeholder
         # Create NSFW placeholder in writable directory
         nsfw_path = "/tmp/NSFW.jpg"
         if not os.path.exists(nsfw_path):
@@ -47,9 +47,9 @@ def load_models():
             base_ckpt="booksforcharlie/stable-diffusion-inpainting",
             attn_ckpt=repo_path,
             attn_ckpt_version="mix",
-            weight_dtype=torch.float16,  # Changed from torch.float32
-            use_tf32=True,  # Changed from False
-            device='cuda'  # Changed from 'cpu'
+            weight_dtype=torch.float16,
+            use_tf32=True,
+            device='cuda'
         )
         print("✅ Pipeline loaded!")
         
@@ -62,18 +62,42 @@ def load_models():
         print("✅ Automasker loaded!")
         
     except Exception as e:
-        print(f"❌ Error loading models: {e}")
-        import traceback
+        print(f"❌ Error loading models: {e}", file=sys.stderr)
         traceback.print_exc()
         raise
 
 def generate_tryon(person_img, cloth_img, progress=gr.Progress()):
     """Generate virtual try-on"""
     
+    # ADD EXTENSIVE LOGGING FOR API DEBUGGING
+    print("=" * 50, file=sys.stderr)
+    print(f"API CALL RECEIVED", file=sys.stderr)
+    print(f"Person image type: {type(person_img)}", file=sys.stderr)
+    print(f"Cloth image type: {type(cloth_img)}", file=sys.stderr)
+    
     if person_img is None or cloth_img is None:
-        raise gr.Error("Please upload both person and garment images!")
+        error_msg = "Please upload both person and garment images!"
+        print(f"ERROR: {error_msg}", file=sys.stderr)
+        raise gr.Error(error_msg)
     
     try:
+        # HANDLE DIFFERENT INPUT TYPES (filepath or PIL)
+        if isinstance(person_img, str):
+            print(f"Converting person_img from filepath: {person_img}", file=sys.stderr)
+            person_img = Image.open(person_img).convert('RGB')
+        elif not isinstance(person_img, Image.Image):
+            print(f"Converting person_img from array", file=sys.stderr)
+            person_img = Image.fromarray(person_img).convert('RGB')
+            
+        if isinstance(cloth_img, str):
+            print(f"Converting cloth_img from filepath: {cloth_img}", file=sys.stderr)
+            cloth_img = Image.open(cloth_img).convert('RGB')
+        elif not isinstance(cloth_img, Image.Image):
+            print(f"Converting cloth_img from array", file=sys.stderr)
+            cloth_img = Image.fromarray(cloth_img).convert('RGB')
+        
+        print(f"Images loaded successfully", file=sys.stderr)
+        
         # Load models
         progress(0.05, desc="Loading models...")
         load_models()
@@ -110,10 +134,14 @@ def generate_tryon(person_img, cloth_img, progress=gr.Progress()):
         
         progress(1.0, desc="Complete! ✨")
         
+        print("SUCCESS: Try-on generated successfully", file=sys.stderr)
         return result
         
     except Exception as e:
-        raise gr.Error(f"Error: {str(e)}")
+        error_msg = f"Error during try-on: {str(e)}"
+        print(f"ERROR: {error_msg}", file=sys.stderr)
+        traceback.print_exc()
+        raise gr.Error(error_msg)
 
 # Create Gradio UI
 with gr.Blocks(
@@ -133,12 +161,12 @@ with gr.Blocks(
             gr.Markdown("### 📸 Inputs")
             person_input = gr.Image(
                 label="👤 Person Image (full body, front-facing)", 
-                type="pil",
+                type="filepath",  # CHANGED FROM "pil" TO "filepath"
                 height=350
             )
             cloth_input = gr.Image(
                 label="👕 Garment Image (flat, white background)", 
-                type="pil",
+                type="filepath",  # CHANGED FROM "pil" TO "filepath"
                 height=350
             )
             
@@ -157,6 +185,7 @@ with gr.Blocks(
             gr.Markdown("### ✨ Result")
             output_img = gr.Image(
                 label="Virtual Try-On Result",
+                type="filepath",  # ADDED type
                 height=700
             )
     
@@ -173,11 +202,12 @@ with gr.Blocks(
     - **GPU T4:** ~2-3 minutes per generation
     """)
     
-    # Event handler
+    # Event handler with API name
     submit_btn.click(
         fn=generate_tryon,
         inputs=[person_input, cloth_input],
-        outputs=output_img
+        outputs=output_img,
+        api_name="generate_tryon"  # ADDED THIS - CRITICAL FOR API ACCESS
     )
 
 # Launch app
@@ -189,5 +219,5 @@ if __name__ == "__main__":
     except Exception as e:
         print(f"⚠️ Model loading will happen on first inference: {e}")
     
-    # Launch with queue
-    demo.queue().launch()
+    # Launch with queue and show_error for better debugging
+    demo.queue().launch(show_error=True)  # ADDED show_error=True