Delete Sapp.py

Sapp.py

@@ -1,76 +0,0 @@
-import streamlit as st
-from PIL import Image
-import numpy as np
-import matplotlib.pyplot as plt
-from cal import load_model, predict_image, calculate_calories
-
-# Load the model
-model = load_model()
-
-# Set up the sidebar
-st.sidebar.title("Food Calorie Detector")
-st.sidebar.write("Upload an image or use your camera to take a picture.")
-
-option = st.sidebar.selectbox(
-    'How would you like to provide the image?',
-    ('Upload an image', 'Use camera')
-)
-
-image_path = None
-if option == 'Upload an image':
-    uploaded_file = st.sidebar.file_uploader("Choose an image...", type=["jpg", "jpeg", "png", "webp"])
-    if uploaded_file is not None:
-        image = Image.open(uploaded_file)
-        if image.mode == 'RGBA':
-            image = image.convert('RGB')
-        image_path = "uploaded_image.jpg"
-        image.save(image_path)
-elif option == 'Use camera':
-    camera_image = st.sidebar.camera_input("Take a picture")
-    if camera_image is not None:
-        image = Image.open(camera_image)
-        if image.mode == 'RGBA':
-            image = image.convert('RGB')
-        image_path = "camera_image.jpg"
-        image.save(image_path)
-
-if image_path:
-    # Display the image and classification results in columns
-    col1, col2 = st.columns(2)
-
-    with col1:
-        st.image(image, caption='Captured Image.', use_column_width=True)
-        st.write("")
-        st.write("Classifying...")
-
-    # Predict the image
-    image_with_boxes, detection_details = predict_image(image_path, model)
-
-    with col2:
-        # Display the image with bounding boxes and labels
-        st.image(image_with_boxes, caption='Processed Image.', use_column_width=True)
-
-    # Calculate and display detected items and their calories
-    detected_items = calculate_calories(detection_details)
-    st.markdown("<h3>Detection Results:</h3>", unsafe_allow_html=True)
-    for item, calories, confidence in detected_items:
-        st.markdown(f"<p style='font-size:18px;'>✓ Detected {item} ({calories} cal/100g) - Confidence: {confidence:.2%}</p>", unsafe_allow_html=True)
-
-# Footer
-st.markdown("""
-    <style>
-        .footer {
-            position: fixed;
-            left: 0;
-            bottom: 0;
-            width: 100%;
-            background-color: #f1f1f1;
-            color: black;
-            text-align: center;
-            padding: 10px;
-        }
-    </style>
-    <div class="footer">
-        <p>Green Food Calorie Detector © 2023</p>
-    </div>
-""", unsafe_allow_html=True)