Update app.py

app.py

@@ -9,25 +9,19 @@ model = load_model('best_automl_model')
 
 # Function to calculate RGB percentages
 def calculate_rgb_percentage(image):
-    """
-    Calculate the Red, Green, and Blue pixel percentages from the cropped conjunctiva portion.
-    """
-    # Convert image to numpy array
     image_array = np.array(image)
     red_channel = image_array[:, :, 0]
     green_channel = image_array[:, :, 1]
     blue_channel = image_array[:, :, 2]
 
-    # Calculate totals
     total_red = np.sum(red_channel)
     total_green = np.sum(green_channel)
     total_blue = np.sum(blue_channel)
     total_rgb = total_red + total_green + total_blue
 
     if total_rgb == 0:
-        return 0, 0, 0  # Avoid division by zero
+        return 0, 0, 0
 
-    # Calculate percentages
     red_percentage = (total_red / total_rgb) * 100
     green_percentage = (total_green / total_rgb) * 100
     blue_percentage = (total_blue / total_rgb) * 100
@@ -36,20 +30,11 @@ def calculate_rgb_percentage(image):
 
 # Function to process image and predict anemia
 def process_image_and_predict(image, x1, y1, x2, y2, sex):
-    """
-    Crop the uploaded eye image based on user-provided coordinates, calculate RGB percentages, and predict anemia.
-    """
     try:
-        # Ensure the image is in RGB format
         image = image.convert("RGB")
-
-        # Crop the image using user-provided coordinates
         cropped_image = image.crop((x1, y1, x2, y2))
-
-        # Calculate RGB percentages
         red_percent, green_percent, blue_percent = calculate_rgb_percentage(cropped_image)
 
-        # Prepare input for anemia prediction
         sex_encoded = 1 if sex == "Male" else 0
         input_data = pd.DataFrame({
             'Red Pixel': [red_percent],
@@ -58,7 +43,6 @@ def process_image_and_predict(image, x1, y1, x2, y2, sex):
             'Sex': [sex_encoded]
         })
 
-        # Predict anemia and probability
         prediction = model.predict(input_data)[0]
         probability = model.predict_proba(input_data)[0][1]
         prediction_label = "Yes" if prediction == 1 else "No"
@@ -78,15 +62,15 @@ def process_image_and_predict(image, x1, y1, x2, y2, sex):
 interface = gr.Interface(
     fn=process_image_and_predict,
     inputs=[
-        gr.Image(type="pil", label="Upload Eye Image"),  # Upload image input
-        gr.Slider(0, 500, step=1, label="X1 (Top-left corner)"),  # X1 coordinate
-        gr.Slider(0, 500, step=1, label="Y1 (Top-left corner)"),  # Y1 coordinate
-        gr.Slider(50, 500, step=1, label="X2 (Bottom-right corner)"),  # X2 coordinate
-        gr.Slider(50, 500, step=1, label="Y2 (Bottom-right corner)"),  # Y2 coordinate
-        gr.Radio(["Male", "Female"], label="Sex"),  # Select Male/Female
+        gr.Image(type="pil", label="Upload Eye Image"),
+        gr.Slider(0, 500, step=1, label="X1 (Top-left corner)"),
+        gr.Slider(0, 500, step=1, label="Y1 (Top-left corner)"),
+        gr.Slider(50, 500, step=1, label="X2 (Bottom-right corner)"),
+        gr.Slider(50, 500, step=1, label="Y2 (Bottom-right corner)"),
+        gr.Radio(["Male", "Female"], label="Sex"),
     ],
     outputs=[
-        gr.Image(type="pil", label="Cropped Conjunctiva"),  # Cropped image output
+        gr.Image(type="pil", label="Cropped Conjunctiva"),
         gr.Text(label="🔴 Red Pixel Percentage"),
         gr.Text(label="🟢 Green Pixel Percentage"),
         gr.Text(label="🔵 Blue Pixel Percentage"),
@@ -98,6 +82,7 @@ interface = gr.Interface(
         "Upload an eye image, adjust the cropping coordinates using sliders, "
         "and predict anemia based on the Red, Green, and Blue pixel percentages."
     ),
+    css="style.css"  # Link the CSS file
 )
 
 # Launch the app