Create app.py

app.py

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+from huggingface_hub import from_pretrained_keras
+import gradio as gr
+
+model = from_pretrained_keras("araeynn/e")
+
+def image_classifier(inp):
+    inp.save("/why.png")
+    sunflower_path = "/why.png"
+    img = tf.keras.utils.load_img(
+      sunflower_path, target_size=(img_height, img_width)
+    )
+    img_array = tf.keras.utils.img_to_array(img)
+    img_array = tf.expand_dims(img_array, 0) # Create a batch
+
+    predictions = model.predict(img_array)
+    score = tf.nn.softmax(predictions)
+    r = {}
+    for class_name in class_names:
+      r[class_name] = score[0][class_names.index(class_name)]
+    return r
+demo = gr.Interface(fn=image_classifier, inputs=gr.Image(type="pil"), outputs="label")
+demo.launch(debug=True)