Create app.py

app.py

@@ -0,0 +1,30 @@
+from PIL import Image
+import cv2
+import numpy as np
+
+import tensorflow as tf
+from keras.models import load_model
+
+import gradio as gr
+
+model =load_model('BrainTumor10Epochs.h5')
+
+def getResult(inp):
+    
+    inp=np.array(inp)
+    input_img = np.expand_dims(inp, axis=0)
+    result=np.max(model.predict(input_img))
+
+    if result==0:
+        return "No Brain Tumor"
+    elif result==1:
+        
+        return "Yes Brain Tumor"
+    
+
+iface=gr.Interface(fn=getResult, 
+             inputs=gr.Image(shape=(64, 64)),
+             outputs=gr.Label(num_top_classes=2),
+             )
+if __name__ == "__main__":
+    iface.launch()