Update app.py

app.py

@@ -34,40 +34,44 @@ def analyze_injury(prediction):
     return severity, treatment, gov_cost, private_cost
 
 # Function to generate report
-def generate_report(patient_name, age, gender, xray1, xray2):
-    # Process X-ray 1
-    img1 = Image.open(xray1).resize(image_size)
-    img_array1 = image.img_to_array(img1)
-    img_array1 = np.expand_dims(img_array1, axis=0) / 255.0  
-    prediction1 = model.predict(img_array1)[0][0]
+def generate_report(patient_name, age, gender, xray1_path, xray2_path):
+    try:
+        # Process X-ray 1
+        img1 = Image.open(xray1_path).resize(image_size)
+        img_array1 = image.img_to_array(img1)
+        img_array1 = np.expand_dims(img_array1, axis=0) / 255.0  
+        prediction1 = model.predict(img_array1)[0][0]
 
-    # Process X-ray 2
-    img2 = Image.open(xray2).resize(image_size)
-    img_array2 = image.img_to_array(img2)
-    img_array2 = np.expand_dims(img_array2, axis=0) / 255.0  
-    prediction2 = model.predict(img_array2)[0][0]
+        # Process X-ray 2
+        img2 = Image.open(xray2_path).resize(image_size)
+        img_array2 = image.img_to_array(img2)
+        img_array2 = np.expand_dims(img_array2, axis=0) / 255.0  
+        prediction2 = model.predict(img_array2)[0][0]
 
-    # Get final analysis
-    avg_prediction = (prediction1 + prediction2) / 2
-    predicted_class = "Fractured" if avg_prediction > 0.5 else "Normal"
-    severity, treatment, gov_cost, private_cost = analyze_injury(avg_prediction)
+        # Get final analysis
+        avg_prediction = (prediction1 + prediction2) / 2
+        predicted_class = "Fractured" if avg_prediction > 0.5 else "Normal"
+        severity, treatment, gov_cost, private_cost = analyze_injury(avg_prediction)
 
-    # Generate PDF
-    report_path = f"{patient_name}_fracture_report.pdf"
-    c = canvas.Canvas(report_path, pagesize=letter)
-    c.setFont("Helvetica", 12)
-    c.drawString(100, 750, f"Patient Name: {patient_name}")
-    c.drawString(100, 730, f"Age: {age}")
-    c.drawString(100, 710, f"Gender: {gender}")
-    c.drawString(100, 690, f"Diagnosis: {predicted_class}")
-    c.drawString(100, 670, f"Injury Severity: {severity}")
-    c.drawString(100, 650, f"Recommended Treatment: {treatment}")
-    c.drawString(100, 630, f"Estimated Cost (Govt Hospital): {gov_cost}")
-    c.drawString(100, 610, f"Estimated Cost (Private Hospital): {private_cost}")
-    
-    c.save()
+        # Generate PDF Report
+        report_path = f"{patient_name}_fracture_report.pdf"
+        c = canvas.Canvas(report_path, pagesize=letter)
+        c.setFont("Helvetica", 12)
+        c.drawString(100, 750, f"Patient Name: {patient_name}")
+        c.drawString(100, 730, f"Age: {age}")
+        c.drawString(100, 710, f"Gender: {gender}")
+        c.drawString(100, 690, f"Diagnosis: {predicted_class}")
+        c.drawString(100, 670, f"Injury Severity: {severity}")
+        c.drawString(100, 650, f"Recommended Treatment: {treatment}")
+        c.drawString(100, 630, f"Estimated Cost (Govt Hospital): {gov_cost}")
+        c.drawString(100, 610, f"Estimated Cost (Private Hospital): {private_cost}")
+        
+        c.save()
+
+        return report_path
 
-    return report_path
+    except Exception as e:
+        return f"Error generating report: {str(e)}"
 
 # Define Gradio Interface
 interface = gr.Interface(
@@ -76,8 +80,8 @@ interface = gr.Interface(
         gr.Textbox(label="Patient Name"),
         gr.Number(label="Age"),
         gr.Radio(["Male", "Female", "Other"], label="Gender"),
-        gr.Image(type="file", label="Upload X-ray Image 1"),
-        gr.Image(type="file", label="Upload X-ray Image 2"),
+        gr.Image(type="filepath", label="Upload X-ray Image 1"),
+        gr.Image(type="filepath", label="Upload X-ray Image 2"),
     ],
     outputs=gr.File(label="Download Report"),
     title="Bone Fracture Detection & Medical Report",