Delete pages/U-Net-Superficial-Intermediate.py

pages/U-Net-Superficial-Intermediate.py

@@ -1,51 +0,0 @@
-import streamlit as st
-import tensorflow as tf
-import cv2
-from PIL import Image, ImageOps
-import numpy as np
-
-# Suppress warnings
-import warnings
-warnings.filterwarnings('ignore', category=UserWarning)
-warnings.filterwarnings('ignore', category=FutureWarning)
-
-def load_model():
-    model = tf.keras.models.load_model('pages/SI_unet_model.keras')
-    return model
-
-with st.spinner('Model is being loaded..'):
-    model = load_model()
-
-st.write("# Image Segmentation U-net Architecture - Superficial-Intermediate Model")
-
-st.sidebar.info("Feel free to select other models from the pages above 🙂")
-
-file = st.file_uploader("Upload the image to be classified", type=["jpg", "png"])
-
-
-def upload_predict(upload_image, model):
-    size = (128, 128)
-    image = ImageOps.fit(upload_image, size, Image.LANCZOS)
-
-    image = image.convert('L')
-
-    image = np.asarray(image)
-
-    image = image / 255.0
-
-    img_reshape = image.reshape(1, 128, 128, 1)
-
-    prediction = model.predict(img_reshape)
-    print(prediction)
-    return prediction
-
-
-if file is None:
-    st.text("Please upload an image file")
-else:
-    image = Image.open(file)
-    st.image(image, use_column_width=True)
-    
-    prediction = upload_predict(image, model)
-    predicted_result = np.argmax(prediction)
-    st.write(f"Predicted class: {predicted_result}")