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Runtime error
| # Demo: (Image) -> (Label) | |
| import gradio as gr | |
| import tensorflow as tf | |
| import numpy as np | |
| import json | |
| from os.path import dirname, realpath, join | |
| # Load human-readable labels for ImageNet. | |
| current_dir = dirname(realpath(__file__)) | |
| with open(join(current_dir, "imagenet_labels.json")) as labels_file: | |
| labels = json.load(labels_file) | |
| mobile_net = tf.keras.applications.MobileNetV2() | |
| def image_classifier(im): | |
| arr = np.expand_dims(im, axis=0) | |
| arr = tf.keras.applications.mobilenet.preprocess_input(arr) | |
| prediction = mobile_net.predict(arr).flatten() | |
| return {labels[i]: float(prediction[i]) for i in range(1000)} | |
| iface = gr.Interface( | |
| image_classifier, | |
| gr.inputs.Image(shape=(224, 224)), | |
| gr.outputs.Label(num_top_classes=3), | |
| capture_session=True, | |
| interpretation="default", | |
| examples=[ | |
| ["cheetah1.jpg"], | |
| ["lion.jpg"], | |
| ["straw.png"], | |
| ["azadi.jpg"] | |
| ]) | |
| if __name__ == "__main__": | |
| iface.launch(share=True) | |