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

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*2+1, blur_value*2+1), 0)
    else:
        processed_img = img_cv
    
    return processed_img

def main():
    st.title("🖼️ Image Processing App 🎨")
    st.markdown("Enhance your images with various effects!")
    
    uploaded_image = st.file_uploader("📤 Upload an image", type=["jpg", "png", "jpeg"])
    
    if uploaded_image is not None:
        image = Image.open(uploaded_image)
        
        st.markdown("### ✏️ Editing Options")
        col3, col4 = st.columns(2)
        
        with col3:
            operation = st.selectbox("🔧 Select an operation", ["None", "Greyscale", "Rotate", "Edge Detection", "Blur"])
        
        rotation_angle = 0
        blur_value = 5
        
        if operation == "Rotate":
            with col4:
                rotation_angle = st.slider("🔄 Rotation Angle", -180, 180, 0)
        elif operation == "Blur":
            with col4:
                blur_value = st.slider("🌫️ Blur Intensity", 1, 25, 5, step=2)
        
        col1, col2 = st.columns(2)
        
        with col1:
            st.image(image, caption="🖼️ Original Image", use_container_width=True)
        
        if operation != "None":
            processed_img = process_image(image, operation, rotation_angle, blur_value)
            
            with col2:
                st.image(processed_img, caption="✨ Processed Image", use_container_width=True, channels="GRAY" if operation == "Greyscale" or operation == "Edge Detection" else "BGR")
                
            processed_pil = Image.fromarray(cv2.cvtColor(processed_img, cv2.COLOR_BGR2RGB) if operation != "Greyscale" and operation != "Edge Detection" else processed_img)
            buf = io.BytesIO()
            processed_pil.save(buf, format="PNG")
            byte_im = buf.getvalue()
            
            st.markdown("### 📥 Download Your Edited Image")
            st.download_button(label="💾 Download", data=byte_im, file_name="processed_image.png", mime="image/png")

if __name__ == "__main__":
    main()