Update app.py

app.py

@@ -155,33 +155,33 @@ def process_image(image, model_choice="GLPN (Recommended)", visualization_type="
         # Check outlier removal
         outlier_pct = (metrics['outliers_removed'] / metrics['initial_points']) * 100
         if outlier_pct < 5:
-            assessment.append("✅ Very clean depth estimation (low noise)")
+            assessment.append("Very clean depth estimation (low noise)")
         elif outlier_pct < 15:
-            assessment.append("✅ Good depth quality (normal noise level)")
+            assessment.append("Good depth quality (normal noise level)")
         else:
-            assessment.append("⚠️ High noise in depth estimation")
+            assessment.append("High noise in depth estimation")
         
         # Check manifold properties
         if metrics['is_edge_manifold'] and metrics['is_vertex_manifold']:
-            assessment.append("✅ Excellent topology - mesh is well-formed")
+            assessment.append("Excellent topology - mesh is well-formed")
         elif metrics['is_vertex_manifold']:
-            assessment.append("⚠️ Good local topology but has some edge issues")
+            assessment.append("Good local topology but has some edge issues")
         else:
-            assessment.append("⚠️ Topology issues present - may need cleanup")
+            assessment.append("Topology issues present - may need cleanup")
         
         # Check watertight
         if metrics['is_watertight']:
-            assessment.append("✅ Watertight mesh - ready for 3D printing!")
+            assessment.append("Watertight mesh - ready for 3D printing!")
         else:
-            assessment.append("ℹ️ Not watertight - use MeshLab's 'Close Holes' for 3D printing")
+            assessment.append("Not watertight - use MeshLab's 'Close Holes' for 3D printing")
         
         # Check complexity
         if metrics['triangles'] > 1000000:
-            assessment.append("ℹ️ Very detailed mesh - may be slow in some software")
+            assessment.append("Very detailed mesh - may be slow in some software")
         elif metrics['triangles'] > 500000:
-            assessment.append("✅ High detail mesh - good quality")
+            assessment.append("High detail mesh - good quality")
         else:
-            assessment.append("✅ Moderate detail - good balance of quality and performance")
+            assessment.append("Moderate detail - good balance of quality and performance")
         
         return "\n".join(f"- {item}" for item in assessment)
     
@@ -513,7 +513,7 @@ def process_image(image, model_choice="GLPN (Recommended)", visualization_type="
         assessment = _generate_quality_assessment(metrics)
         
         report = f"""
-## Reconstruction Complete! ✅
+## Reconstruction Complete!
 
 ### Performance Metrics
 - **Model Used**: {metrics['model_used']}
@@ -543,7 +543,7 @@ def process_image(image, model_choice="GLPN (Recommended)", visualization_type="
 - Mesh: PLY, OBJ, STL formats
 - Quality Metrics: JSON
 
-**Download the complete package below! 📦**
+**Download the complete package below!**
         """
         
         print("SUCCESS! Returning results...")
@@ -573,7 +573,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
     with gr.Tabs():
         
         # ========== RECONSTRUCTION TAB ==========
-        with gr.Tab("🎯 Reconstruction"):
+        with gr.Tab("Reconstruction"):
             with gr.Row():
                 with gr.Column(scale=1):
                     input_image = gr.Image(type="pil", label="Upload Image")
@@ -591,7 +591,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
                         label="3D Visualization Type"
                     )
                     
-                    reconstruct_btn = gr.Button("🚀 Start Reconstruction", variant="primary", size="lg")
+                    reconstruct_btn = gr.Button("Start Reconstruction", variant="primary", size="lg")
                 
                 with gr.Column(scale=2):
                     depth_output = gr.Image(label="Depth Map Comparison")
@@ -604,7 +604,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
                     json_output = gr.Textbox(label="Raw Metrics (JSON)", lines=10)
             
             with gr.Row():
-                download_output = gr.File(label="📦 Download Complete Package (ZIP)")
+                download_output = gr.File(label="Download Complete Package (ZIP)")
             
             reconstruct_btn.click(
                 fn=process_image,
@@ -613,7 +613,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
             )
         
        # ========== THEORY TAB ==========
-        with gr.Tab("📚 Theory & Background"):
+        with gr.Tab("Theory & Background"):
             gr.Markdown(THEORY_TEXT)
             
             gr.Markdown("""
@@ -652,8 +652,8 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
             
             | Feature | GLPN (Recommended) | DPT (High Quality) |
             |---------|-------------------|-------------------|
-            | **Speed** | ⚡ Fast (~0.3-2.5s) | 🐢 Slower (~0.8-6.5s) |
-            | **Quality** | ⭐⭐⭐⭐ Good | ⭐⭐⭐⭐⭐ Excellent |
+            | **Speed** | Fast (~0.3-2.5s) | Slower (~0.8-6.5s) |
+            | **Quality** | Good |  Excellent |
             | **Memory** | Low (~2GB) | High (~5GB) |
             | **Best For** | Indoor scenes, Real-time | Complex scenes, Highest quality |
             | **Training** | NYU Depth V2 | Multiple datasets |
@@ -674,7 +674,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
             """)
         
         # ========== USAGE GUIDE TAB ==========
-        with gr.Tab("📖 Usage Guide"):
+        with gr.Tab("Usage Guide"):
             gr.Markdown("""
             ## How to Use This Application
             
@@ -700,7 +700,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
             - **Both**: Shows both mesh and point cloud together
             
             ### Step 4: Start Reconstruction
-            - Click "🚀 Start Reconstruction" button
+            - Click "Start Reconstruction" button
             - Wait for processing (typically 10-60 seconds total)
             - Watch for status messages in the console/logs
             - Results appear automatically when complete
@@ -767,7 +767,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
             
             ## Tips for Best Results
             
-            ### ✅ DO:
+            ### DO:
             - Use well-lit images without harsh shadows
             - Include visible depth cues (corners, edges, varying distances)
             - Use images of indoor scenes (rooms, furniture, objects)
@@ -775,7 +775,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
             - Use medium resolution (512-1024px is ideal)
             - Take photos perpendicular to main surfaces
             
-            ### ❌ AVOID:
+            ### AVOID:
             - Motion blur or very low resolution images
             - Reflective surfaces (mirrors, polished metal, glass)
             - Completely uniform textures (solid white wall)
@@ -831,7 +831,7 @@ with gr.Blocks(title="Advanced 3D Reconstruction", theme=gr.themes.Soft()) as de
             - For 3D printing: use mesh repair in MeshLab
           """)
         # ========== CITATION TAB ==========
-        with gr.Tab("📄 Citation & Credits"):
+        with gr.Tab("Citation & Credits"):
             gr.Markdown("""