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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() | |