Add batch/sequence processing: view segmentation sequence for multiple images from same subject

app.py

@@ -264,21 +264,57 @@ def load_demo_file():
     else:
         return None, "⚠️ Demo file not found. Please upload a medical image file (DICOM, PNG, or JPG)."
 
-def process_with_status(dicom_file, prompt_text, modality, window_type):
+def process_with_status(image_file, prompt_text, modality, window_type):
     """Wrapper function to update status during processing."""
     if model is None or processor is None:
         return None, "❌ Error: Model not loaded."
     
-    if dicom_file is None:
+    if image_file is None:
         return None, "⚠️ Please upload a medical image file (DICOM, PNG, or JPG) or load the demo file."
     
-    result = process_medical_image(dicom_file, prompt_text, modality, window_type)
+    result = process_medical_image(image_file, prompt_text, modality, window_type)
     
     if result is None:
         return None, "❌ Processing failed. Check console for error details."
     else:
         return result, "✅ Segmentation complete!"
 
+def process_sequence(image_files, prompt_text, modality, window_type):
+    """Process multiple images from the same subject and return gallery of results."""
+    if model is None or processor is None:
+        return [], "❌ Error: Model not loaded."
+    
+    if not image_files:
+        return [], "⚠️ Please upload medical image files (DICOM, PNG, or JPG)."
+    
+    # Handle single file or list of files
+    if isinstance(image_files, str):
+        image_files = [image_files]
+    
+    results = []
+    status_messages = []
+    
+    for idx, image_file in enumerate(image_files):
+        if image_file is None:
+            continue
+            
+        status_msg = f"Processing image {idx + 1}/{len(image_files)}..."
+        status_messages.append(status_msg)
+        
+        result = process_medical_image(image_file, prompt_text, modality, window_type)
+        
+        if result:
+            results.append(result)
+            status_messages.append(f"✅ Image {idx + 1} segmented successfully")
+        else:
+            status_messages.append(f"❌ Failed to process image {idx + 1}")
+    
+    if results:
+        status = f"✅ Processed {len(results)}/{len(image_files)} images successfully!\n" + "\n".join(status_messages)
+        return results, status
+    else:
+        return [], "❌ No images were processed successfully. Check console for error details."
+
 with gr.Blocks() as demo:
     gr.Markdown("# 🏥 NeuroSAM 3: Medical Image Segmentation")
     
@@ -304,58 +340,113 @@ with gr.Blocks() as demo:
     - PNG/JPG - Standard image formats (works with Kaggle brain MRI datasets)
     """)
     
-    with gr.Row():
-        with gr.Column():
-            file_input = gr.File(
-                label="Upload Medical Image (DICOM .dcm, PNG, JPG)", 
-                file_types=[".dcm", ".png", ".jpg", ".jpeg"],
-                type="filepath",
-                value=demo_file_path
-            )
-            
-            load_demo_btn = gr.Button(
-                "📁 Load Demo File", 
-                variant="secondary", 
-                size="sm",
-                visible=bool(demo_file_path)
-            )
-            
-            text_input = gr.Textbox(
-                label="Text Prompt", 
-                value="brain", 
-                placeholder="e.g. brain, tumor, skull, eyes",
-                info="Describe what anatomical structure or region you want to segment"
-            )
-            
+    with gr.Tabs():
+        with gr.Tab("Single Image"):
             with gr.Row():
-                modality_dropdown = gr.Dropdown(
-                    ["CT", "MRI"], 
-                    label="Modality", 
-                    value="MRI",
-                    info="Select the imaging modality"
-                )
-                window_dropdown = gr.Dropdown(
-                    ["Brain (Grey Matter)", "Bone (Skull)", "Soft Tissue (Face)"], 
-                    label="Windowing Strategy (CT only)", 
-                    value="Brain (Grey Matter)",
-                    info="CT windowing preset (ignored for MRI)"
-                )
-            
-            submit_btn = gr.Button("Segment Structure", variant="primary", size="lg")
-            
-        with gr.Column():
-            image_output = gr.Image(
-                label="Segmentation Result",
-                type="filepath"
-            )
-            
-            gr.Markdown("### Status")
-            status_text = gr.Textbox(
-                label="Processing Status",
-                value="Ready. Upload a medical image file (DICOM, PNG, or JPG) to begin.",
-                interactive=False
-            )
+                with gr.Column():
+                    file_input = gr.File(
+                        label="Upload Medical Image (DICOM .dcm, PNG, JPG)", 
+                        file_types=[".dcm", ".png", ".jpg", ".jpeg"],
+                        type="filepath",
+                        value=demo_file_path
+                    )
+                    
+                    load_demo_btn = gr.Button(
+                        "📁 Load Demo File", 
+                        variant="secondary", 
+                        size="sm",
+                        visible=bool(demo_file_path)
+                    )
+                    
+                    text_input = gr.Textbox(
+                        label="Text Prompt", 
+                        value="brain", 
+                        placeholder="e.g. brain, tumor, skull, eyes",
+                        info="Describe what anatomical structure or region you want to segment"
+                    )
+                    
+                    with gr.Row():
+                        modality_dropdown = gr.Dropdown(
+                            ["CT", "MRI"], 
+                            label="Modality", 
+                            value="MRI",
+                            info="Select the imaging modality"
+                        )
+                        window_dropdown = gr.Dropdown(
+                            ["Brain (Grey Matter)", "Bone (Skull)", "Soft Tissue (Face)"], 
+                            label="Windowing Strategy (CT only)", 
+                            value="Brain (Grey Matter)",
+                            info="CT windowing preset (ignored for MRI)"
+                        )
+                    
+                    submit_btn = gr.Button("Segment Structure", variant="primary", size="lg")
+                    
+                with gr.Column():
+                    image_output = gr.Image(
+                        label="Segmentation Result",
+                        type="filepath"
+                    )
+                    
+                    gr.Markdown("### Status")
+                    status_text = gr.Textbox(
+                        label="Processing Status",
+                        value="Ready. Upload a medical image file (DICOM, PNG, or JPG) to begin.",
+                        interactive=False
+                    )
+        
+        with gr.Tab("Sequence / Batch Processing"):
+            gr.Markdown("**Process multiple images from the same subject to see segmentation sequence**")
+            with gr.Row():
+                with gr.Column():
+                    files_input = gr.File(
+                        label="Upload Multiple Images (Select multiple files)", 
+                        file_types=[".dcm", ".png", ".jpg", ".jpeg"],
+                        file_count="multiple",
+                        type="filepath"
+                    )
+                    
+                    text_input_batch = gr.Textbox(
+                        label="Text Prompt", 
+                        value="brain", 
+                        placeholder="e.g. brain, tumor, skull, eyes",
+                        info="Describe what anatomical structure or region you want to segment"
+                    )
+                    
+                    with gr.Row():
+                        modality_dropdown_batch = gr.Dropdown(
+                            ["CT", "MRI"], 
+                            label="Modality", 
+                            value="MRI",
+                            info="Select the imaging modality"
+                        )
+                        window_dropdown_batch = gr.Dropdown(
+                            ["Brain (Grey Matter)", "Bone (Skull)", "Soft Tissue (Face)"], 
+                            label="Windowing Strategy (CT only)", 
+                            value="Brain (Grey Matter)",
+                            info="CT windowing preset (ignored for MRI)"
+                        )
+                    
+                    submit_batch_btn = gr.Button("Process Sequence", variant="primary", size="lg")
+                    
+                with gr.Column():
+                    gallery_output = gr.Gallery(
+                        label="Segmentation Sequence Results",
+                        show_label=True,
+                        elem_id="gallery",
+                        columns=2,
+                        rows=2,
+                        height="auto"
+                    )
+                    
+                    gr.Markdown("### Batch Status")
+                    status_batch_text = gr.Textbox(
+                        label="Processing Status",
+                        value="Ready. Upload multiple medical image files to process a sequence.",
+                        interactive=False,
+                        lines=5
+                    )
 
+    # Single image processing
     load_demo_btn.click(
         fn=load_demo_file,
         inputs=[],
@@ -367,6 +458,13 @@ with gr.Blocks() as demo:
         inputs=[file_input, text_input, modality_dropdown, window_dropdown],
         outputs=[image_output, status_text]
     )
+    
+    # Batch/sequence processing
+    submit_batch_btn.click(
+        fn=process_sequence,
+        inputs=[files_input, text_input_batch, modality_dropdown_batch, window_dropdown_batch],
+        outputs=[gallery_output, status_batch_text]
+    )
 
 if __name__ == "__main__":
     demo.launch()