create the file

app.py

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+import gradio as gr
+import numpy as np
+from tensorflow.keras.models import load_model
+from PIL import Image
+
+# Load the model
+model = load_model("hf_keras_model.keras")
+class_names = ['buildings', 'forest', 'glacier', 'mountain', 'sea', 'street']
+
+def predict_image(img):
+    img = img.resize((150, 150))
+    img_array = np.array(img) / 255.0
+    img_array = np.expand_dims(img_array, axis=0)
+    preds = model.predict(img_array)[0]
+    confidences = {class_names[i]: float(preds[i]) for i in range(6)}
+    return confidences
+
+gr.Interface(
+    fn=predict_image,
+    inputs=gr.Image(type="pil"),
+    outputs=gr.Label(num_top_classes=3),
+    title="Intel Image Classifier",
+    description="Upload a landscape image and get predictions (buildings, forest, glacier, etc.)"
+).launch()