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| import streamlit as st | |
| from PIL import Image | |
| import cv2 | |
| import numpy as np | |
| def save_image(): | |
| # st.title("Image Processing and Saving Example") | |
| # Upload an image using Streamlit's file uploader | |
| genre = st.radio( | |
| "How You Want To Upload Your Image", | |
| ('Browse Photos', 'Camera')) | |
| if genre == 'Camera': | |
| uploaded_image = st.camera_input("Take a picture") | |
| else: | |
| uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"]) | |
| # uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"]) | |
| if uploaded_image is not None: | |
| # Display the uploaded image | |
| # st.image(uploaded_image, caption="Uploaded Image", use_column_width=True) | |
| # Convert the image to a format compatible with PIL and OpenCV | |
| pil_image = Image.open(uploaded_image) | |
| opencv_image = np.array(pil_image) | |
| opencv_image = cv2.cvtColor(opencv_image, cv2.COLOR_BGR2RGB) | |
| # Image processing code (You can add any processing you want here) | |
| # Save the processed image using PIL | |
| # st.write("Processed Image") | |
| # st.image(pil_image, caption="Processed Image", use_column_width=True) | |
| # Save the processed image using OpenCV | |
| # save_button = st.button("Save Processed Image") | |
| # if save_button: | |
| # Provide a file path to save the image | |
| save_path = "processed_image.jpg" # You can change the file format or filename here | |
| cv2.imwrite(save_path, opencv_image) | |
| st.success(f"Image saved as {save_path}") | |
| # if __name__ == "__main__": | |
| # main() | |