Create app.py

app.py

@@ -0,0 +1,19 @@
+import tensorflow as tf 
+from PIL import Image
+import numpy as np 
+import streamlit as st 
+
+img = st.file_uploader("Choose a file")
+model = tf.keras.models.load_model('RockPaperScissor.h5')
+if img is not None:
+    img = Image.open(img)
+    img = img.resize((256,256))
+    img = np.reshape(img,(1,256,256,3))
+    pred = model.predict(img)
+    pred = np.argmax(pred)
+    if pred == 0:
+        st.write('PAPER')
+    elif pred == 1:
+        st.write('ROCK')
+    elif:
+        st.write('SCISSOR')