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

# Function to process the image
def process_image(image, operation, value=None):
    if operation == "🖼 Original":
        return image
    elif operation == "⚫ Convert to Grayscale":
        return cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
    elif operation == "🌈 Convert to Color":
        return cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    elif operation == "🔄 Rotate":
        if value is not None:
            return rotate_image_without_cropping(image, value)
    elif operation == "🌀 Blur":
        if value is not None:
            kernel_size = (value, value)
            return cv2.GaussianBlur(image, kernel_size, 0)
    elif operation == "✂ Edge Detection":
        return cv2.Canny(image, 100, 200)
    elif operation == "☀ Adjust Brightness":
        if value is not None:
            hsv = cv2.cvtColor(image, cv2.COLOR_RGB2HSV)
            h, s, v = cv2.split(hsv)
            v = np.clip(v.astype(np.int16) + value, 0, 255).astype(np.uint8)
            final_hsv = cv2.merge((h, s, v))
            return cv2.cvtColor(final_hsv, cv2.COLOR_HSV2RGB)
    return image

# Fix rotation issue (avoids cropping & mirroring)
def rotate_image_without_cropping(image, angle):
    (h, w) = image.shape[:2]
    center = (w // 2, h // 2)

    # Compute the rotation matrix
    M = cv2.getRotationMatrix2D(center, angle, 1.0)

    # Compute the new bounding box size
    cos = np.abs(M[0, 0])
    sin = np.abs(M[0, 1])
    new_w = int((h * sin) + (w * cos))
    new_h = int((h * cos) + (w * sin))

    # Adjust transformation matrix to fit in new bounds
    M[0, 2] += (new_w / 2) - center[0]
    M[1, 2] += (new_h / 2) - center[1]

    # Apply rotation with expanded borders
    rotated = cv2.warpAffine(image, M, (new_w, new_h), borderMode=cv2.BORDER_CONSTANT, borderValue=(0, 0, 0))

    return rotated

# Streamlit app
def main():
    st.title(" Image Processing App ")
    st.write("📂 Upload an image and apply various transformations below! ✨")

    uploaded_file = st.file_uploader("📤 Choose an image...", type=["jpg", "jpeg", "png"])

    if uploaded_file is not None:
        # Read image
        image = Image.open(uploaded_file)
        img_array = np.array(image)
        img_bgr = cv2.cvtColor(img_array, cv2.COLOR_RGB2BGR)

        col1, col2 = st.columns(2)

        with col1:
            st.subheader("📌 Original Image")
            st.image(image, use_container_width=True)

        with col2:
            st.subheader("🖌 Processed Image")

            operation = st.selectbox(
                "🎛 Select an Operation",
                ["🖼 Original", "⚫ Convert to Grayscale", "🌈 Convert to Color", 
                 "🔄 Rotate", "🌀 Blur", "✂ Edge Detection", "☀ Adjust Brightness"]
            )

            processed_img = img_bgr.copy()

            if operation == "🔄 Rotate":
                angle = st.slider("↩ Rotation Angle", -180, 180, 0)
                processed_img = process_image(img_bgr, operation, angle)
            elif operation == "☀ Adjust Brightness":
                brightness = st.slider("🔆 Brightness Level", -100, 100, 0)
                processed_img = process_image(img_bgr, operation, brightness)
            elif operation == "🌀 Blur":
                blur_level = st.slider("🎭 Blur Intensity", 1, 25, 5, step=2)  # Ensures odd kernel size
                processed_img = process_image(img_bgr, operation, blur_level)
            else:
                processed_img = process_image(img_bgr, operation)

            # Convert back to RGB
            if len(processed_img.shape) == 2:
                processed_img_rgb = cv2.cvtColor(processed_img, cv2.COLOR_GRAY2RGB)
            else:
                processed_img_rgb = cv2.cvtColor(processed_img, cv2.COLOR_BGR2RGB)

            st.image(processed_img_rgb, use_container_width=True)

        # Ensure grayscale images are properly handled before download
        if len(processed_img.shape) == 2:
            processed_img = cv2.cvtColor(processed_img, cv2.COLOR_GRAY2BGR)

        is_success, buffer = cv2.imencode(".png", processed_img)
        if is_success:
            st.download_button(
                label="📥 Download Processed Image",
                data=buffer.tobytes(),
                file_name="processed_image.png",
                mime="image/png"
            )

if __name__ == "__main__":
    main()