Create classifier.py

classifier.py

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+import tensorflow as tf
+from tf.keras.models import load_model
+model = load_model('myModel.hdf5')
+
+import gradio as gr
+
+def classify(inp):
+  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[0])
+  confidences = {class_names[i]: float(score[i]) for i in range(5)}
+  return confidences
+
+gr.Interface(fn=classify, 
+             inputs=gr.Image(shape=(180, 180)),
+             outputs=gr.Label(num_top_classes=5)).launch(debug=True)
+