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import gradio as gr
import tensorflow as tf
import numpy as np
from PIL import Image
import tensorflow.keras as keras
#import keras.applications.vgg16 as vgg16
from tensorflow.keras.models import load_model
model=load_model("model2.h5")
classnames=["Fire","Non-Fire"]
def predict_image(img):
img_4d=img.reshape(-1,180,180,3)
prediction=model.predict(img_4d)[0]
return {classnames[i]: float(prediction[i] for i in range(2))}
image=gr.inputs.Image(shape=(180))
label=gr.outputs.Label(num_top_classes=2)
article="<p style='text-align: center'>Made by Mahak xoxo</p>"
gr.Interface(fn=predict_image,inputs=image,title="Forest Fire Classifier",description="This is a forest fire classification model ",outputs=label,article=article,enable_queue=True,interpretation='default').launch()
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