Update pages/model_1.py

pages/model_1.py

@@ -19,23 +19,26 @@ with st.spinner('Model is being loaded..'):
 st.title("CNN Model")
 st.write("model loaded")
     
-# file = st.file_uploader("Upload the image to be classified", type=["jpg", "png"])
-# st.set_option('deprecation.showfileUploaderEncoding', False)
+file = st.file_uploader("Upload the image to be classified", type=["jpg", "png"])
+st.set_option('deprecation.showfileUploaderEncoding', False)
 
 
-# def upload_predict(upload_image, model):
-#     size = (180, 180)
-#     image = ImageOps.fit(upload_image, size, Image.LANCZOS)
-#     image = np.asarray(image)
-#     img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
-#     img_resize = cv2.resize(img, dsize=(224, 224), interpolation=cv2.INTER_CUBIC)
+def upload_predict(upload_image, model):
+    size = (180, 180)
+    image = ImageOps.fit(upload_image, size, Image.LANCZOS)
+    image = np.asarray(image)
+    img = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
+    img_resize = cv2.resize(img, dsize=(224, 224), interpolation=cv2.INTER_CUBIC)
 
-#     img_reshape = img_resize[np.newaxis, ...]
+    img_reshape = img_resize[np.newaxis, ...]
 
-#     prediction = model.predict(img_reshape)
-#     print(prediction)
-#     return prediction
+    prediction = model.predict(img_reshape)
+    print(prediction)
+    return prediction
 
 
-# if file is None:
-#     st.text("Please upload an image file")
+if file is None:
+    st.text("Please upload an image file")
+else:
+    image = Image.open(file)
+    st.image(image, use_column_width=True)