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Runtime error
| import gradio as gr | |
| import tensorflow as tf | |
| from huggingface_hub import from_pretrained_keras | |
| import numpy as np | |
| model = from_pretrained_keras("keras-io/mobile-vit-xxs") | |
| classes=['dandelion','daisy','tulip','sunflower','rose'] | |
| image_size = 256 | |
| def classify_images(image): | |
| image = tf.convert_to_tensor(image) | |
| image = tf.image.resize(image, (image_size, image_size)) | |
| image = tf.expand_dims(image,axis=0) | |
| prediction = model.predict(image) | |
| prediction = tf.squeeze(tf.round(prediction)) | |
| text_output = str(f'{classes[(np.argmax(prediction))]}!') | |
| return text_output | |
| i = gr.inputs.Image() | |
| o = gr.outputs.Textbox() | |
| examples = [["./examples/tulip.png"], ["./examples/daisy.jpeg"], ["./examples/dandelion.jpeg"], ["./examples/rose.png"], ["./examples/sunflower.png"]] | |
| title = "Flowers Classification MobileViT" | |
| description = "Upload an image or select from examples to classify flowers" | |
| article = "<div style='text-align: center;'><a href='https://twitter.com/SatpalPatawat' target='_blank'>Space by Satpal Singh Rathore</a><br><a href='https://keras.io/examples/vision/mobilevit/' target='_blank'>Keras example by Sayak Paul</a></div>" | |
| gr.Interface(classify_images, i, o, allow_flagging=False, analytics_enabled=False, | |
| title=title, examples=examples, description=description, article=article).launch(enable_queue=True) |