commit

pp.py

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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
+
+
+from tensorflow.keras.models import load_model
+
+model=load_model("model1.h5")
+
+classnames=["Fire","Non-Fire"]
+
+def predict_image(img):
+    img_4d=img.reshape(-1,180,180,3)
+    prediction=model.predict(img_4d)[0]
+    return {classname[i]: float(prediction[i] for i in range(2))}
+
+image=gr.inputs.Image(shape=(180,180))
+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 ",article=article,outputs=label,enable_queue=True,interpretation='default').launch(share=True)
+