import streamlit as st
import cv2
import numpy as np
from PIL import Image

def process_image(image, operation, rotation_angle=0, blur_value=5):
    img_array = np.array(image)
    img_cv = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)
    
    if operation == "Greyscale":
        processed_img = cv2.cvtColor(img_cv, cv2.COLOR_BGR2GRAY)
    elif operation == "Rotate":
        (h, w) = img_cv.shape[:2]
        center = (w // 2, h // 2)
        M = cv2.getRotationMatrix2D(center, rotation_angle, 1.0)
        processed_img = cv2.warpAffine(img_cv, M, (w, h))
    elif operation == "Edge Detection":
        processed_img = cv2.Canny(img_cv, 100, 200)
    elif operation == "Blur":
        processed_img = cv2.GaussianBlur(img_cv, (blur_value, blur_value), 0)
    else:
        processed_img = img_cv
    
    return processed_img

def main():
    st.title("Image Processing App")
    uploaded_image = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
    
    if uploaded_image is not None:
        image = Image.open(uploaded_image)
        st.image(image, caption="Original Image", use_container_width=True)
        
        operation = st.selectbox("Select an operation", ["None", "Greyscale", "Rotate", "Edge Detection", "Blur"])
        
        rotation_angle = 0
        blur_value = 5
        
        if operation == "Rotate":
            rotation_angle = st.slider("Select Rotation Angle", -180, 180, 0)
        elif operation == "Blur":
            blur_value = st.slider("Select Blur Intensity", 1, 25, 5, step=2)
        
        if operation != "None":
            processed_img = process_image(image, operation, rotation_angle, blur_value)
            st.image(processed_img, caption="Processed Image", use_container_width=True, channels="GRAY" if operation == "Greyscale" or operation == "Edge Detection" else "BGR")

if __name__ == "__main__":
    main()