biomedparse+biomedllama_3b_multimodal

app.py

@@ -382,14 +382,18 @@ def process_image(image_path, user_prompt, modality=None):
                 
                 # Add color mapping to analysis with more natural language
                 color_descriptions = []
+                # First loop: collect prompts found in the analysis
+                found_prompts = []
                 for idx, prompt in enumerate(relevant_prompts):
                     if prompt in detailed_analysis.lower():
                         color = colors[idx % len(colors)]
                         color_name = {(255,0,0): "red", (0,255,0): "green", (0,0,255): "blue", 
                                     (255,255,0): "yellow", (255,0,255): "magenta"}[color]
                         color_descriptions.append(f"The {prompt} is highlighted in {color_name} color")
+                        found_prompts.append(prompt)
                 
-                for idx, prompt in enumerate(relevant_prompts):
+                # Second loop: only process prompts found in analysis
+                for idx, prompt in enumerate(found_prompts):
                     try:
                         mask_list = interactive_infer_image(model, pil_image, [prompt])
                         if mask_list is None or len(mask_list) == 0:
@@ -413,7 +417,7 @@ def process_image(image_path, user_prompt, modality=None):
                         analysis_results.append(f"Failed to process '{prompt}': {str(e)}")
                 
                 if not results:
-                    results = [image]  # Return original image if no overlays were created       
+                    results = [image]  # Return original image if no overlays were created
                 detailed_analysis += "\n\nIn the segmentation analysis:"
                 if color_descriptions:
                     detailed_analysis += " " + " ".join(color_descriptions) + "."