Update app.py

app.py

@@ -1,7 +1,6 @@
 import gradio as gr
 import tensorflow as tf
 import numpy as np
-import cv2
 from tensorflow.keras.preprocessing import image
 from PIL import Image, ImageDraw
 from reportlab.lib.pagesizes import letter
@@ -14,21 +13,17 @@ model = tf.keras.models.load_model("my_keras_model.h5")
 # Define image size
 image_size = (224, 224)
 
-# Function to detect fracture and get bounding box
+# Function to detect fracture
 def detect_fracture(xray):
     img = Image.open(xray).convert("RGB").resize(image_size)
     img_array = image.img_to_array(img) / 255.0
     img_array = np.expand_dims(img_array, axis=0)
-    
+
     prediction = model.predict(img_array)[0][0]
-    
-    # Dummy bounding box for now (assuming model enhancement needed)
-    # Ideally, the model should return bounding box coordinates
     bbox = (50, 50, 150, 150) if prediction > 0.5 else None  # Placeholder
-    
     return prediction, bbox, img
 
-# Function to analyze injury severity
+# Function to analyze severity
 def analyze_injury(prediction):
     if prediction < 0.3:
         severity = "Mild"
@@ -45,12 +40,11 @@ def analyze_injury(prediction):
         treatment = "Major surgery with metal implants, extensive physiotherapy."
         gov_cost = "₹20,000 - ₹50,000"
         private_cost = "₹1,00,000+"
-    
+
     return severity, treatment, gov_cost, private_cost
 
 # Function to generate report
 def generate_report(name, age, gender, xray1, xray2):
-    # Analyze X-ray images
     prediction1, bbox1, img1 = detect_fracture(xray1)
     prediction2, bbox2, img2 = detect_fracture(xray2)
 
@@ -58,7 +52,7 @@ def generate_report(name, age, gender, xray1, xray2):
     diagnosed_class = "Fractured" if avg_prediction > 0.5 else "Normal"
     severity, treatment, gov_cost, private_cost = analyze_injury(avg_prediction)
 
-    # Draw bounding box if fracture is detected
+    # Draw bounding box if fracture detected
     if bbox1:
         draw = ImageDraw.Draw(img1)
         draw.rectangle(bbox1, outline="red", width=5)
@@ -67,7 +61,7 @@ def generate_report(name, age, gender, xray1, xray2):
         draw = ImageDraw.Draw(img2)
         draw.rectangle(bbox2, outline="red", width=5)
 
-    # Save modified images
+    # Save images
     img1_path = f"{name}_xray1.png"
     img2_path = f"{name}_xray2.png"
     img1.save(img1_path)
@@ -91,30 +85,65 @@ def generate_report(name, age, gender, xray1, xray2):
 
     return report_path, img1_path, img2_path, diagnosed_class, severity, treatment, gov_cost, private_cost
 
-# Define Gradio interface
-interface = gr.Interface(
-    fn=generate_report,
-    inputs=[
-        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"),
-    ],
-    outputs=[
-        gr.File(label="Download Report"),
-        gr.Image(label="X-ray 1 with Fracture Highlight"),
-        gr.Image(label="X-ray 2 with Fracture Highlight"),
-        gr.Textbox(label="Fracture Detected"),
-        gr.Textbox(label="Injury Severity"),
-        gr.Textbox(label="Recommended Treatment"),
-        gr.Textbox(label="Estimated Cost (Govt Hospital)"),
-        gr.Textbox(label="Estimated Cost (Private Hospital)")
-    ],
-    title="Bone Fracture Detection & Medical Report",
-    description="Enter patient details, upload two X-ray images, and generate a detailed medical report with treatment suggestions and cost estimates."
-)
-
-# Launch the app
+# UI Components
+with gr.Blocks() as app:
+    gr.Markdown("# 🏥 Bone Fracture Detection & Medical Report")
+    gr.Markdown(
+        "### A radiologist is a doctor who specializes in reading medical images like X-rays, MRIs, and CT scans to diagnose diseases and injuries."
+    )
+    gr.Image("x.jpg", label="X-Ray Example")
+    gr.Markdown(
+        """
+        ## **Understanding Bone Fractures**
+        - **Closed (Simple):** Bone doesn't pierce skin.
+        - **Open (Compound):** Bone breaks skin.
+        - **Hairline:** Small stress fracture.
+        - **Comminuted:** Bone shatters into pieces.
+        - **Avulsion:** Tendon pulls bone fragment.
+        - **Compression:** Bones forced together.
+        """
+    )
+    gr.Markdown(
+        """
+        ## **First Aid**
+        - Immobilize the injured area.
+        - Control bleeding, cover wounds.
+        - Don't straighten broken bones.
+        - Use splints, slings for support.
+        - Apply cold packs.
+        - Seek emergency help.
+        """
+    )
+
+    with gr.Row():
+        gr.Markdown("## 📝 Patient Information Form")
+
+    with gr.Column():
+        name = gr.Textbox(label="Patient Name")
+        age = gr.Number(label="Age")
+        gender = gr.Radio(["Male", "Female", "Other"], label="Gender")
+
+    with gr.Column():
+        xray1 = gr.Image(type="file", label="Upload X-ray Image 1")
+        xray2 = gr.Image(type="file", label="Upload X-ray Image 2")
+
+    submit_button = gr.Button("Generate Report")
+
+    output_file = gr.File(label="Download Report")
+    xray1_output = gr.Image(label="X-ray 1 with Fracture Highlight")
+    xray2_output = gr.Image(label="X-ray 2 with Fracture Highlight")
+    diagnosis_output = gr.Textbox(label="Fracture Detected")
+    severity_output = gr.Textbox(label="Injury Severity")
+    treatment_output = gr.Textbox(label="Recommended Treatment")
+    gov_cost_output = gr.Textbox(label="Estimated Cost (Govt Hospital)")
+    private_cost_output = gr.Textbox(label="Estimated Cost (Private Hospital)")
+
+    submit_button.click(
+        generate_report,
+        inputs=[name, age, gender, xray1, xray2],
+        outputs=[output_file, xray1_output, xray2_output, diagnosis_output, severity_output, treatment_output, gov_cost_output, private_cost_output],
+    )
+
+# Run app
 if __name__ == "__main__":
-    interface.launch()
+    app.launch()