Add application files

app.py

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+import gradio as gr
+
+import tensorflow as tf
+import numpy as np
+
+
+MODEL = tf.keras.models.load_model("my_model")
+CLASS_NAMES = ['circle', 'rectangle']
+
+
+def classify_predict(inp):
+    image = inp
+    image_batch = np.expand_dims(image, 0)
+    predictions = MODEL.predict(image_batch)
+    values, indices = tf.math.top_k(predictions, 2)
+    predicted_values = values.numpy().tolist()[0]
+    indcs = indices.numpy().tolist()[0]
+    confidences = {CLASS_NAMES[i]: round(v, 4) for i, v in zip(indcs, predicted_values)}
+    print(confidences)
+    return confidences
+
+
+interface = gr.Interface(
+    fn=classify_predict,
+    inputs=gr.inputs.Image(shape=(64, 64)),
+    outputs="label",
+    examples=["28.jpg", "57.jpg"]
+)
+
+interface.launch()

requirements.txt

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+tensorflow
+numpy