diff --git a/app.py b/app.py index 60e26ffd92345b58eebfbb4011301a06be53b335..a1c00278162c0e9a3eba58157870c7af0b877ac9 100644 --- a/app.py +++ b/app.py @@ -180,29 +180,49 @@ model = initialize_model() @torch.inference_mode() @torch.autocast(device_type="cuda", dtype=torch.bfloat16) def process_image(image_path, text_prompts, modality): - image = read_rgb(image_path) - text_prompts = [prompt.strip() for prompt in text_prompts.split(',')] - - # Run inference - pred_masks = interactive_infer_image(model, Image.fromarray(image), text_prompts) - - # Prepare outputs - results = [] - dice_scores = [] - p_values = [] + try: + # Input validation + if not image_path: + raise ValueError("Please upload an image") + if not text_prompts or text_prompts.strip() == "": + raise ValueError("Please enter prompts for analysis") + if not modality: + raise ValueError("Please select a modality") + + image = read_rgb(image_path) + text_prompts = [prompt.strip() for prompt in text_prompts.split(',')] + + # Run inference + pred_masks = interactive_infer_image(model, Image.fromarray(image), text_prompts) + + # Prepare outputs + results = [] + p_values = [] + + for i, prompt in enumerate(text_prompts): + # Calculate p-value for the selected modality + print("PROMPT: ", prompt, flush=True) + p_value = check_mask_stats(image, pred_masks[i] * 255, modality, prompt) + p_values.append(f"P-value for '{prompt}' ({modality}): {p_value:.4f}") - for i, prompt in enumerate(text_prompts): - # Calculate p-value for the selected modality - print("PROMPT: ", prompt, flush=True) - p_value = check_mask_stats(image, pred_masks[i] * 255, modality, prompt) - p_values.append(f"P-value for '{prompt}' ({modality}): {p_value:.4f}") + # Overlay predictions on the image + overlay_image = image.copy() + overlay_image[pred_masks[i] > 0.5] = [255, 0, 0] # Highlight predictions in red + results.append(overlay_image) - # Overlay predictions on the image - overlay_image = image.copy() - overlay_image[pred_masks[i] > 0.5] = [255, 0, 0] # Highlight predictions in red - results.append(overlay_image) + return results, "\n".join(p_values) - return results, p_values + except ValueError as ve: + # Handle validation errors + return None, f"⚠️ Input Error: {str(ve)}" + except torch.cuda.OutOfMemoryError: + # Handle CUDA out of memory errors + return None, "⚠️ Error: GPU memory exceeded. Please try with a smaller image." + except Exception as e: + # Handle all other errors + error_msg = f"��️ An error occurred: {str(e)}" + print(f"Error details: {str(e)}", flush=True) # For logging + return None, error_msg # Define Gradio interface with gr.Blocks() as demo: @@ -210,7 +230,11 @@ with gr.Blocks() as demo: with gr.Row(): with gr.Column(): image_input = gr.Image(type="filepath", label="Input Image") - prompts_input = gr.Textbox(lines=2, placeholder="Enter prompts separated by commas...", label="Prompts") + prompts_input = gr.Textbox( + lines=2, + placeholder="Enter prompts separated by commas...", + label="Prompts" + ) modality_dropdown = gr.Dropdown( choices=list(BIOMEDPARSE_MODES.keys()), value=list(BIOMEDPARSE_MODES.keys())[0], @@ -219,28 +243,18 @@ with gr.Blocks() as demo: submit_btn = gr.Button("Submit") with gr.Column(): output_gallery = gr.Gallery(label="Findings") - pvalue_output = gr.Textbox(label="Confidence (P-values)", interactive=False) + pvalue_output = gr.Textbox( + label="Results", + interactive=False, + show_label=True + ) + # Add error handling for the submit button submit_btn.click( - process_image, + fn=process_image, inputs=[image_input, prompts_input, modality_dropdown], - outputs=[output_gallery, pvalue_output] + outputs=[output_gallery, pvalue_output], + api_name="process" ) - # with gr.Row(): - # gr.Examples( - # fn=process_image, - # examples=IMAGE_PROCESSING_EXAMPLES, - # inputs=[ - # image_processing_mode_dropdown_component, - # image_processing_image_input_component, - # image_processing_text_input_component - # ], - # outputs=[ - # image_processing_image_output_component, - # image_processing_text_output_component - # ], - # run_on_click=True - # ) - -# Launch the app + demo.launch() \ No newline at end of file diff --git a/inference_utils/__pycache__/__init__.cpython-39.pyc b/inference_utils/__pycache__/__init__.cpython-39.pyc new file mode 100644 index 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