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app.py

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+import gradio as gr
+from PIL import Image
+import numpy as np
+from pycaret.classification import load_model
+
+# Load the saved anemia prediction model
+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)
+    
+    # Extract R, G, B channels
+    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
+    
+    # Avoid division by zero
+    if total_rgb == 0:
+        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
+    
+    return round(red_percentage, 2), round(green_percentage, 2), round(blue_percentage, 2)
+
+# Function to process image and predict anemia
+def process_image_and_predict(image, sex):
+    """
+    Process the uploaded eye image, calculate RGB percentages, and predict anemia.
+    """
+    # Ensure the image is in RGB format
+    image = image.convert("RGB")
+    
+    # Crop image interactively (default cropping for now)
+    cropped_image = image.crop((50, 50, 250, 250))  # Modify coordinates if necessary
+    
+    # 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  # Encode Male as 1, Female as 0
+    input_data = pd.DataFrame({
+        'Red Pixel': [red_percent],
+        'Green Pixel': [green_percent],
+        'Blue Pixel': [blue_percent],
+        'Sex': [sex_encoded]
+    })
+    
+    # Predict anemia and probability
+    prediction = model.predict(input_data)[0]
+    probability = model.predict_proba(input_data)[0][1]
+    
+    # Convert prediction result to human-readable format
+    prediction_label = "Yes" if prediction == 1 else "No"
+    
+    return (
+        cropped_image,
+        f"Red: {red_percent}%",
+        f"Green: {green_percent}%",
+        f"Blue: {blue_percent}%",
+        prediction_label,
+        f"{probability:.2%}"
+    )
+
+# Create Gradio Interface
+interface = gr.Interface(
+    fn=process_image_and_predict,
+    inputs=[
+        gr.Image(type="pil", label="Upload or Capture Eye Image"),
+        gr.Radio(["Male", "Female"], label="Sex"),
+    ],
+    outputs=[
+        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"),
+        gr.Text(label="🩺 Anemia Prediction"),
+        gr.Text(label="📊 Probability of Anemia (%)"),
+    ],
+    title="✨ Conjunctiva-Based Anemia Prediction App ✨",
+    description=(
+        "Upload or capture an eye image, crop the conjunctiva portion, calculate the percentages of Red, "
+        "Green, and Blue pixels, and predict anemia based on these percentages and sex."
+    ),
+    theme="huggingface",  # Use Hugging Face theme
+    css="style.css",  # Link custom CSS for styling
+    examples=[
+        ["example_eye.jpg", "Male"],  
+        ["example_eye.jpg", "Female"],
+    ],
+)
+
+# Launch the app
+interface.launch()

best_automl_model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b2380025f163eeb045e823c58b5ce95106d54622ee3b460c6f7bfd89657c4d70
+size 4375

requirements.txt

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+gradio
+pycaret
+pillow
+numpy
+pandas
+scikit-learn

style.css

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+/* Set background color */
+body {
+    background-color: #f7f7f7;
+    font-family: "Arial", sans-serif;
+}
+
+/* Style the title */
+h1 {
+    color: #2c3e50;
+    text-align: center;
+    font-size: 2.5em;
+    margin-bottom: 10px;
+}
+
+/* Style the description */
+.gr-description {
+    text-align: center;
+    color: #34495e;
+    font-size: 1.2em;
+    margin-bottom: 20px;
+}
+
+/* Customize the buttons */
+button {
+    background-color: #3498db !important;
+    color: white !important;
+    border: none;
+    padding: 10px 20px !important;
+    border-radius: 5px !important;
+    font-size: 1em !important;
+    cursor: pointer;
+}
+
+/* Style text outputs */
+.gr-output-text {
+    font-size: 1.1em;
+    font-weight: bold;
+    color: #2c3e50;
+}