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