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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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model = tf.keras.models.load_model("D:\\repos\\tf.arabic\mymodel\mymodel") |
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def predict(img): |
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z = tf.keras.preprocessing.image.img_to_array(img) |
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z = np.expand_dims(z, axis=0) |
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print(z.shape, z) |
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y = model.predict(z) |
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ysoft = tf.nn.softmax(y) |
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ymax = np.argmax(ysoft) |
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return ymax |
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sp = gr.Sketchpad(shape=(140,100), image_mode="L", label='arabic numeral').style(height=400, width=400) |
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gr.Label() |
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gr.Interface(fn=predict, |
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inputs=sp, |
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outputs="label", |
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share=True, |
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live=True, |
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examples=[ |
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["writer001_pass01_digit2.png"], |
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["writer001_pass01_digit4.png"], |
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["writer001_pass07_digit9.png"], |
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["writer594_pass06_digit7.png"]]).launch() |