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

# Page configuration
st.set_page_config(
    page_title="AI Image Enhancement Tool",
    page_icon="🖼️",
    layout="wide"
)

st.title("🖼️ AI Based Image Enhancement Application")
st.markdown("Enhance brightness, contrast and remove noise from your images in real-time.")

# Sidebar controls
st.sidebar.header("Enhancement Controls")

brightness = st.sidebar.slider("Brightness (Beta)", 0, 100, 50)
contrast = st.sidebar.slider("Contrast (Alpha)", 1.0, 3.0, 1.5)
blur = st.sidebar.slider("Noise Reduction (Gaussian Blur)", 1, 15, 5, step=2)

uploaded_file = st.file_uploader("Upload an Image", type=["jpg","jpeg","png"])

def enhance_image(image, alpha, beta, blur_value):
    image_np = np.array(image)
    image_np = cv2.cvtColor(image_np, cv2.COLOR_RGB2BGR)

    enhanced = cv2.convertScaleAbs(image_np, alpha=alpha, beta=beta)
    denoised = cv2.GaussianBlur(enhanced, (blur_value, blur_value), 0)

    final = cv2.cvtColor(denoised, cv2.COLOR_BGR2RGB)
    return final

if uploaded_file is not None:

    image = Image.open(uploaded_file)

    col1, col2 = st.columns(2)

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

    processed = enhance_image(image, contrast, brightness, blur)

    with col2:
        st.subheader("Enhanced Image")
        st.image(processed, use_column_width=True)

    result = Image.fromarray(processed)

    buf = io.BytesIO()
    result.save(buf, format="PNG")
    byte_im = buf.getvalue()

    st.download_button(
        label="📥 Download Enhanced Image",
        data=byte_im,
        file_name="enhanced_image.png",
        mime="image/png"
    )

st.markdown("---")
st.markdown("Built using Streamlit + OpenCV")