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import gradio as gr
import cv2
from keras.models import load_model
my_model=load_model('Liver_model.h5',compile=True)
class_num={0:'Healthy',1:'Un-Healthy'}
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
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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