Create app.py

app.py

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+from tensorflow.keras.models import load_model
+from PIL import Image
+import numpy as np 
+import tensorflow as tf
+import streamlit as st 
+
+model = load_model('AgeClassifier.h5')
+model2 = load_model('GenderClassifier.h5')
+# Open the video file
+f = st.file_uploader("Choose a Photo")
+    # Read the video file from the file-like object
+if f is not None:
+    img = Image.open(f)
+    img = img.resize((256,256))
+    img = np.reshape(img,(1,28,28,3))
+    pred,pred2 = model.predict(img),model2.predict(img)
+    
+    st.image(img,use_column_width=True)
+    st.write(np.argmax(pred))
+    if pred2[0]>= 0.5:
+        st.write('Male')
+    else:
+        st.write('Female')
+