more fixes

app.py

@@ -30,67 +30,77 @@ except:
 # Check if complex dependencies are installed
 def check_complex_dependencies():
     """Check if complex dependencies are available"""
+    dependencies_ok = True
+    missing_deps = []
+    
     try:
         import nvdiffrast
+        print("✓ nvdiffrast available")
+    except ImportError:
+        print("✗ nvdiffrast not available")
+        dependencies_ok = False
+        missing_deps.append("nvdiffrast")
+    
+    try:
         import pytorch3d
-        
-        # Check if torch-sparse is available or disabled
-        try:
-            import torch_sparse
-        except ImportError:
-            # Check if torch-sparse was disabled
-            try:
-                with open("NeuralJacobianFields/PoissonSystem.py", 'r') as f:
-                    content = f.read()
-                if "USE_TORCH_SPARSE = False" in content:
-                    print("torch-sparse is disabled, using built-in PyTorch sparse operations")
-                else:
-                    return False
-            except:
-                return False
-        
-        # Check if torch-scatter is available (not critical)
-        try:
-            import torch_scatter
-        except ImportError:
-            print("torch-scatter not available, but this may not be critical")
-        
-        # Try to safely import torchvision
+        print("✓ pytorch3d available")
+    except ImportError:
+        print("✗ pytorch3d not available")
+        dependencies_ok = False
+        missing_deps.append("pytorch3d")
+    
+    # Check if torch-sparse is available or disabled
+    try:
+        import torch_sparse
+        print("✓ torch-sparse available")
+    except ImportError:
+        # Check if torch-sparse was disabled
         try:
-            import torchvision
-            print(f"torchvision {torchvision.__version__} loaded successfully")
-        except RuntimeError as e:
-            if "operator torchvision::nms does not exist" in str(e):
-                print("WARNING: Compatibility issue with torchvision. Will attempt to continue anyway.")
+            with open("NeuralJacobianFields/PoissonSystem.py", 'r') as f:
+                content = f.read()
+            if "USE_TORCH_SPARSE = False" in content:
+                print("✓ torch-sparse is disabled, using built-in PyTorch sparse operations")
             else:
-                print(f"WARNING: torchvision error: {e}")
-        except ImportError:
-            print("WARNING: torchvision not available")
-            
-        return True
-    except ImportError as e:
-        print(f"Dependency error: {e}")
-        return False
-
-# Run post-install if needed
-if not check_complex_dependencies():
-    print("Complex dependencies not found, running post-install...")
+                print("✗ torch-sparse not available")
+                missing_deps.append("torch-sparse")
+        except:
+            print("✗ torch-sparse not available")
+            missing_deps.append("torch-sparse")
+    
+    # Check if torch-scatter is available (not critical)
     try:
-        import subprocess
-        subprocess.run([sys.executable, "post_install.py"], check=True)
-        print("Post-install completed successfully!")
-        
-        # Run test to verify installation
-        print("Running installation test...")
-        subprocess.run([sys.executable, "test_installation.py"], check=True)
-        print("Installation test passed!")
-        
-        print("Restarting to pick up new dependencies...")
-        # Restart the process to pick up new dependencies
-        os.execv(sys.executable, ['python'] + sys.argv)
-    except Exception as e:
-        print(f"Post-install failed: {e}")
-        sys.exit(1)
+        import torch_scatter
+        print("✓ torch-scatter available")
+    except ImportError:
+        print("⚠ torch-scatter not available, but this may not be critical")
+    
+    # Try to safely import torchvision
+    try:
+        import torchvision
+        print(f"✓ torchvision {torchvision.__version__} loaded successfully")
+    except RuntimeError as e:
+        if "operator torchvision::nms does not exist" in str(e):
+            print("⚠ Compatibility issue with torchvision. Will attempt to continue anyway.")
+        else:
+            print(f"⚠ torchvision error: {e}")
+    except ImportError:
+        print("⚠ torchvision not available")
+    
+    if missing_deps:
+        print(f"Missing dependencies: {', '.join(missing_deps)}")
+    
+    return dependencies_ok
+
+# Check dependencies but don't fail if some are missing
+print("Checking dependencies...")
+deps_ok = check_complex_dependencies()
+
+if not deps_ok:
+    print("Some dependencies are missing, but continuing anyway...")
+    print("The app will start with limited functionality.")
+    print("You can install missing dependencies manually if needed.")
+else:
+    print("All dependencies are available!")
 
 # Enhanced torchvision compatibility handling
 def apply_torchvision_fix():
@@ -192,6 +202,7 @@ if import_success:
 else:
     print(f"�� Processing engine failed to load: {loop_import_error}")
     print("The interface will still start, but processing functionality will be limited.")
+    print("This is normal in Dev Mode if dependencies are still being installed.")
 
 # Ensure NeuralJacobianFields is properly configured
 try:
@@ -602,8 +613,8 @@ def create_interface():
             engine_status = "✅ Processing engine loaded successfully"
             status_msg = "Ready to generate garments. Select an input method and click 'Generate 3D Garment'."
         else:
-            engine_status = f"❌ Processing engine unavailable: {loop_import_error or 'Unknown error'}"
-            status_msg = "Processing engine is currently unavailable. Please check the system status."
+            engine_status = f"⚠️ Processing engine unavailable: {loop_import_error or 'Unknown error'}"
+            status_msg = "Processing engine is currently unavailable. This is normal in Dev Mode if dependencies are still being installed. The interface will work once dependencies are ready."
         
         engine_status_output = gr.Markdown(f"**System Status:** {engine_status}")
         status_output = gr.Markdown(status_msg)