Create app.py

app.py

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+import gradio as gr
+import numpy as np
+import tensorflow as tf
+from tensorflow import keras
+
+# Load the trained model
+siamese = keras.models.load_model("siamese_model.keras")
+
+# Load stored images for comparison
+stored_images = [
+    np.load("mun_image.npy"),  # Preprocessed image of Munzali
+    np.load("bas_image.npy"),  # Preprocessed image of Bash
+    np.load("usa_image.npy"),  # Preprocessed image of Usama
+]
+stored_imgs = [np.expand_dims(img, axis=0) for img in stored_images]
+
+# Inference function
+def check_membership(uploaded_image):
+    uploaded_image = np.expand_dims(uploaded_image, axis=0)
+    predictions = [siamese.predict([uploaded_image, img])[0][0] for img in stored_imgs]
+    if predictions[0] < 0.5:
+        return "You are welcome Munzali"
+    elif predictions[1] < 0.5:
+        return "You are welcome Ahmad"
+    elif predictions[2] < 0.5:
+        return "You are welcome Usama"
+    else:
+        return "You are not a member"
+
+# Gradio interface
+iface = gr.Interface(
+    fn=check_membership,
+    inputs=gr.Image(shape=(160, 160)),
+    outputs="text",
+    title="Siamese Network Membership Check",
+    description="Upload an image to check if you are a member.",
+)
+
+iface.launch()