| import gradio as gr |
| import cv2 |
| from keras.models import load_model |
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| my_model=load_model('Liver_model.h5',compile=True) |
| class_num={0:'Healthy',1:'Un-Healthy'} |
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| def Predict(Image): |
| Image=cv2.resize(Image,(224,224)) |
| class_no=my_model.predict(Image.reshape(1,224,224,3)).argmax() |
| class_name=class_num.get(class_no) |
| return class_name |
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| interface=gr.Interface(fn=Predict,inputs='image',outputs=[gr.components.Textbox(label="Class Name")], |
| title="This Space predict the liver of Chicken is healthy or un-healthy", |
| examples=[['Test1.jpg'],['Test2.jpeg'],['Test3.jpeg']]) |
| interface.launch(debug=True) |
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