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Update app.py
Browse files
app.py
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@@ -21,9 +21,38 @@ except FileNotFoundError:
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# --- Core Logic Functions (Unchanged and Correct) ---
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async def process_analysis(patient_name, patient_age, image_list, is_sample=False):
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async def refresh_history_table():
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# --- Gradio UI Definition ---
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css = """
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# --- Core Logic Functions (Unchanged and Correct) ---
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async def process_analysis(patient_name, patient_age, image_list, is_sample=False):
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if not is_sample and (not patient_name or patient_age is None):
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raise gr.Error("Patient Name and Age are required.")
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if not image_list:
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raise gr.Error("At least one image is required.")
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result = prediction_pipeline.predict(image_list)
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if "error" in result:
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raise gr.Error(result.get("details", result["error"]))
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final_pred = result["final_prediction"]
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final_conf = result["final_confidence"]
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if not is_sample:
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await add_patient_record(str(patient_name), int(patient_age), final_pred, final_conf)
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confidences = {"NORMAL": 0.0, "PNEUMONIA": 0.0}
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confidences[final_pred] = final_conf
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confidences["NORMAL" if final_pred == "PNEUMONIA" else "PNEUMONIA"] = 1 - final_conf
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return [
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gr.update(visible=False),
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gr.update(visible=True),
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gr.update(value=result["watermarked_images"]),
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gr.update(value=confidences)
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]
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async def refresh_history_table():
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records = await get_all_records()
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data_for_df = []
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if records:
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data_for_df = [[r.get('name'), r.get('age'), r.get('prediction_result'), f"{r.get('confidence_score', 0):.2%}", r.get('timestamp').strftime('%Y-%m-%d %H:%M')] for r in records]
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return gr.update(value=data_for_df)
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# --- Gradio UI Definition ---
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css = """
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