| import gradio as gr |
| from tensorflow import keras as k |
| import numpy as np |
|
|
| loaded_CNN = k.models.load_model('Digit_classification_model2.h5') |
|
|
| def predict(img): |
| img_array = np.array(img) |
| img_array = img_array.reshape(1, 28, 28) |
| img_array = img_array/255 |
| pred = loaded_CNN.predict(img_array) |
| print(pred) |
| return np.argmax(pred) |
|
|
| iface = gr.Interface(predict, inputs = 'sketchpad', |
| outputs = 'text', |
| allow_flagging = 'never', |
| description = 'Project : Recognizing hardwritten digits : Draw a Single Digit Below... (Draw in the middle for Better results)') |
| |
| iface.launch(debug = "True", width = 500, height = 500) |
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