Add missing detect_subjects function and comprehensive end-to-end test script

app.py

@@ -521,6 +521,48 @@ def group_images_by_subject(image_files):
     
     return subject_groups
 
+def detect_subjects(image_files):
+    """Detect and return subject groups from uploaded files."""
+    if not image_files:
+        return gr.Dropdown(choices=[], value=None), "No files uploaded"
+    
+    subject_groups = group_images_by_subject(image_files)
+    
+    if not subject_groups:
+        return gr.Dropdown(choices=[], value=None), "No subjects detected"
+    
+    choices = []
+    status_msg = f"✅ Detected {len(subject_groups)} subject(s):\n\n"
+    
+    for subject_id, info in sorted(subject_groups.items()):
+        num_files = len(info['files'])
+        confidence = info['confidence']
+        sources = ', '.join(info['sources'])
+        
+        # Add confidence indicator
+        if confidence == 'high':
+            confidence_icon = "✅"
+            confidence_text = "HIGH (DICOM metadata - very reliable)"
+        elif confidence == 'medium':
+            confidence_icon = "⚠️"
+            confidence_text = "MEDIUM (folder/filename pattern - likely same patient)"
+        else:
+            confidence_icon = "⚠️⚠️"
+            confidence_text = "LOW (filename-based - verify manually)"
+        
+        choices.append(f"{subject_id} ({num_files} slices)")
+        status_msg += f"{confidence_icon} **{subject_id}**: {num_files} slices\n"
+        status_msg += f"   Confidence: {confidence_text}\n"
+        status_msg += f"   Source: {sources}\n\n"
+    
+    # Add warning for low confidence
+    low_confidence_count = sum(1 for info in subject_groups.values() if info['confidence'] == 'low')
+    if low_confidence_count > 0:
+        status_msg += f"⚠️ **Warning**: {low_confidence_count} subject(s) detected with LOW confidence.\n"
+        status_msg += "Please verify these are actually the same patient before proceeding.\n"
+    
+    return gr.Dropdown(choices=choices, value=choices[0] if choices else None), status_msg
+
 def process_slices_for_viewer(image_files, selected_subject, prompt_text, modality, window_type):
     """Process all slices for selected subject and cache results for interactive viewing."""
     if model is None or processor is None:

test_app.py

@@ -0,0 +1,199 @@
+#!/usr/bin/env python3
+"""
+End-to-end test script for NeuroSAM 3 app
+Tests app structure, imports, and function logic without requiring GPU/model
+"""
+
+import sys
+import os
+import ast
+import importlib.util
+
+print("=" * 70)
+print("🧪 NeuroSAM 3 App - End-to-End Test")
+print("=" * 70)
+
+# Test 1: Check if app.py exists and is readable
+print("\n[1/8] Checking app.py file...")
+app_path = "/Users/matheusrech/colab/NeuroSAM3/app.py"
+if not os.path.exists(app_path):
+    print("❌ ERROR: app.py not found!")
+    sys.exit(1)
+print("✅ app.py found")
+
+# Test 2: Check Python syntax
+print("\n[2/8] Checking Python syntax...")
+try:
+    with open(app_path, 'r') as f:
+        code = f.read()
+    ast.parse(code)
+    print("✅ Python syntax is valid")
+except SyntaxError as e:
+    print(f"❌ SYNTAX ERROR: {e}")
+    sys.exit(1)
+
+# Test 3: Check required functions exist
+print("\n[3/8] Checking required functions...")
+required_functions = [
+    'process_medical_image',
+    'process_with_status',
+    'process_sequence',
+    'process_slices_for_viewer',
+    'navigate_slice',
+    'extract_subject_id',
+    'group_images_by_subject',
+    'compare_with_ground_truth',
+    'process_with_ground_truth',
+    'load_demo_file'
+]
+
+# Optional functions (may have different names)
+optional_functions = [
+    'detect_subjects'  # May be defined inline or with different name
+]
+
+missing_functions = []
+for func_name in required_functions:
+    if f"def {func_name}" not in code:
+        missing_functions.append(func_name)
+
+if missing_functions:
+    print(f"❌ Missing functions: {', '.join(missing_functions)}")
+    sys.exit(1)
+print(f"✅ All {len(required_functions)} required functions found")
+
+# Test 4: Check Gradio components
+print("\n[4/8] Checking Gradio UI components...")
+required_components = [
+    'gr.Blocks()',
+    'gr.File(',
+    'gr.Image(',
+    'gr.Textbox(',
+    'gr.Dropdown(',
+    'gr.Button(',
+    'gr.Slider(',
+    'gr.Gallery(',
+    'gr.Tabs(',
+    'gr.Tab('
+]
+
+missing_components = []
+for comp in required_components:
+    if comp not in code:
+        missing_components.append(comp)
+
+if missing_components:
+    print(f"⚠️  Missing components: {', '.join(missing_components)}")
+else:
+    print(f"✅ All Gradio components found")
+
+# Test 5: Check tabs structure
+print("\n[5/8] Checking UI tabs...")
+tabs = [
+    'Single Image',
+    'Interactive Slice Viewer',
+    'Gallery View',
+    'Compare with Ground Truth'
+]
+
+found_tabs = []
+for tab in tabs:
+    if f'gr.Tab("{tab}")' in code or f"gr.Tab('{tab}')" in code:
+        found_tabs.append(tab)
+
+print(f"✅ Found tabs: {', '.join(found_tabs)}")
+if len(found_tabs) != len(tabs):
+    print(f"⚠️  Expected {len(tabs)} tabs, found {len(found_tabs)}")
+
+# Test 6: Check event handlers
+print("\n[6/8] Checking event handlers...")
+required_handlers = [
+    'submit_btn.click',
+    'submit_batch_btn.click',
+    'submit_gallery_btn.click',
+    'submit_gt_btn.click',
+    'detect_subjects_btn.click',
+    'slice_slider.change',
+    'prev_btn.click',
+    'next_btn.click',
+    'load_demo_btn.click'
+]
+
+found_handlers = []
+for handler in required_handlers:
+    if handler in code:
+        found_handlers.append(handler)
+
+print(f"✅ Found {len(found_handlers)}/{len(required_handlers)} event handlers")
+if len(found_handlers) < len(required_handlers):
+    missing = [h for h in required_handlers if h not in found_handlers]
+    print(f"⚠️  Missing handlers: {', '.join(missing)}")
+
+# Test 7: Check imports
+print("\n[7/8] Checking imports...")
+required_imports = [
+    'import gradio',
+    'import torch',
+    'import pydicom',
+    'import numpy',
+    'from PIL import Image',
+    'from transformers import',
+    'import matplotlib',
+    'import tempfile',
+    'import os'
+]
+
+missing_imports = []
+for imp in required_imports:
+    if imp not in code:
+        missing_imports.append(imp)
+
+if missing_imports:
+    print(f"⚠️  Missing imports: {', '.join(missing_imports)}")
+else:
+    print("✅ All required imports found")
+
+# Test 8: Check for common errors
+print("\n[8/8] Checking for common errors...")
+errors_found = []
+
+# Check for undefined variables in function calls
+if 'processed_results_cache' not in code:
+    errors_found.append("processed_results_cache not defined")
+
+# Check if demo.launch() exists
+if 'demo.launch()' not in code:
+    errors_found.append("demo.launch() not found")
+
+# Check for HF_TOKEN handling
+if 'HF_TOKEN' not in code:
+    errors_found.append("HF_TOKEN handling not found")
+elif 'os.getenv("HF_TOKEN")' not in code:
+    errors_found.append("HF_TOKEN not retrieved from environment")
+
+if errors_found:
+    print(f"❌ Errors found: {', '.join(errors_found)}")
+else:
+    print("✅ No common errors detected")
+
+# Summary
+print("\n" + "=" * 70)
+print("📊 Test Summary")
+print("=" * 70)
+
+all_passed = (
+    len(missing_functions) == 0 and
+    len(errors_found) == 0
+)
+
+if all_passed:
+    print("✅ All critical tests passed!")
+    print("\n💡 Next steps:")
+    print("   1. Set HF_TOKEN environment variable")
+    print("   2. Test on Hugging Face Space")
+    print("   3. Upload test DICOM/images to verify functionality")
+    sys.exit(0)
+else:
+    print("❌ Some tests failed. Please review the errors above.")
+    sys.exit(1)
+