| import gradio as gr | |
| import numpy as np | |
| import tensorflow as tf | |
| import tensorflow_hub as hub | |
| loaded_model = tf.keras.models.load_model( | |
| ('CatDogmodel2.h5'), | |
| custom_objects={'KerasLayer':hub.KerasLayer} | |
| ) | |
| def model(image): | |
| im_scaled = image/255 | |
| im_reshape = np.reshape(im_scaled,[1,160,160,3]) | |
| pred = loaded_model.predict(im_reshape) | |
| pred_label = np.argmax(pred) | |
| if (pred_label == 0): | |
| return "The Image is of a Dog." | |
| if (pred_label == 1): | |
| return "The Image is of a Cat." | |
| image = gr.inputs.Image(shape=(160,160)) | |
| css_code='body{background-image:url("https://cdn.shopify.com/s/files/1/0017/4024/2996/articles/the-magic-of-black-cats-dogs-188729.png?v=1606316714");}' | |
| iface = gr.Interface(fn=model, inputs=image, outputs='text', css=css_code) | |
| iface.launch(debug=True) | |