Intial commit

app.py

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+import gradio as gr
+import tensorflow as tf
+from PIL import Image
+import numpy as np
+
+# Load the models
+model1 = tf.keras.models.load_model('face_detection_model1.h5')
+model2 = tf.keras.models.load_model('face_detection_model2.h5')
+
+def preprocess_image(image):
+    img = Image.fromarray(image.astype('uint8'), 'RGB')
+    img = img.resize((150, 150))
+    img_array = np.array(img) / 255.0
+    return np.expand_dims(img_array, axis=0)
+
+def predict_image(image):
+    preprocessed_image = preprocess_image(image)
+    
+    # Make predictions using both models
+    pred1 = model1.predict(preprocessed_image)[0][0]
+    pred2 = model2.predict(preprocessed_image)[0][0]
+    
+    # Average the predictions
+    avg_pred = (pred1 + pred2) / 2
+    
+    result = "Real" if avg_pred > 0.5 else "Fake"
+    confidence = avg_pred if avg_pred > 0.5 else 1 - avg_pred
+    
+    return f"{result} (Confidence: {confidence:.2f})"
+
+iface = gr.Interface(
+    fn=predict_image,
+    inputs=gr.Image(),
+    outputs="text",
+    title="Real vs Fake Face Detection",
+    description="Upload an image to determine if it's a real or fake face."
+)
+
+iface.launch()

requirements.txt

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+tensorflow==2.9.1
+gradio==3.32.0
+Pillow==9.5.0
+numpy==1.24.3