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import gradio as gr |
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import tensorflow as tf |
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import numpy as np |
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import json |
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from os.path import dirname, realpath, join |
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current_dir = dirname(realpath(file)) |
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with open(join(current_dir, "imagenet_labels.json")) as labels_file: |
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labels = json.load(labels_file) |
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mobile_net = tf.keras.applications.MobileNetV2() |
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def image_classifier(im): |
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arr = np.expand_dims(im, axis=0) |
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arr = tf.keras.applications.mobilenet.preprocess_input(arr) |
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prediction = mobile_net.predict(arr).flatten() |
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return {labels[i]: float(prediction[i]) for i in range(1000)} |
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iface = gr.Interface( |
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image_classifier, |
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gr.inputs.Image(shape=(224, 224)), |
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gr.outputs.Label(num_top_classes=3), |
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capture_session=True, |
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interpretation="default", |
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examples=[ |
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["cheetah1.jpg"], |
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["lion.jpg"], |
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["ma.jpg"] |
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]) |
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if name == "main": |
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iface.launch(share=True) |
