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| import tensorflow as tf | |
| import numpy as np | |
| from urllib.request import urlretrieve | |
| import gradio as gr | |
| urlretrieve("https://gr-models.s3-us-west-2.amazonaws.com/mnist-model.h5", "mnist-model.h5") | |
| model = tf.keras.models.load_model("mnist-model.h5") | |
| def recognize_digit(image): | |
| image = image.reshape(1, -1) # add a batch dimension | |
| prediction = model.predict(image).tolist()[0] | |
| return {str(i): prediction[i] for i in range(10)} | |
| gr.Interface(fn=recognize_digit, | |
| inputs="sketchpad", | |
| outputs=gr.outputs.Label(num_top_classes=3), | |
| live=True, | |
| css=".footer {display:none !important}", | |
| # title="MNIST Sketchpad", | |
| description="Draw a number 0 through 9 on the sketchpad, and see predictions in real time.", | |
| thumbnail="https://raw.githubusercontent.com/gradio-app/real-time-mnist/master/thumbnail2.png").launch(); | |