app.py

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

# Load model files
prototxt_path = "colorization_deploy_v2.prototxt"
model_path = "colorization_release_v2.caffemodel"
kernel_path = "pts_in_hull.npy"

# Load the model
net = cv2.dnn.readNetFromCaffe(prototxt_path, model_path)
points = np.load(kernel_path)
points = points.transpose().reshape(2, 313, 1, 1)
net.getLayer(net.getLayerId("class8_ab")).blobs = [points.astype(np.float32)]
net.getLayer(net.getLayerId("conv8_313_rh")).blobs = [np.full([1, 313], 2.686, dtype="float32")]

# Streamlit App
st.title("Black-and-White Image Colorization")
st.write("Upload a black-and-white image to colorize it.")

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

if uploaded_file is not None:
    # Convert uploaded file to OpenCV format
    image = Image.open(uploaded_file)
    bw_image = np.array(image.convert("RGB"))
    bw_image = cv2.cvtColor(bw_image, cv2.COLOR_RGB2BGR)

    # Preprocessing for colorization
    normalized = bw_image.astype("float32") / 255.0
    lab = cv2.cvtColor(normalized, cv2.COLOR_BGR2LAB)
    resized = cv2.resize(lab, (224, 224))
    L = cv2.split(resized)[0]
    L -= 55

    # Predict color channels
    net.setInput(cv2.dnn.blobFromImage(L))
    ab = net.forward()[0, :, :, :].transpose((1, 2, 0))
    ab = cv2.resize(ab, (bw_image.shape[1], bw_image.shape[0]))

    # Combine L and ab channels
    L = cv2.split(lab)[0]
    colorized = np.concatenate((L[:, :, np.newaxis], ab), axis=2)

    # Convert LAB to BGR
    colorized = cv2.cvtColor(colorized, cv2.COLOR_LAB2BGR)
    colorized = (255 * colorized).astype("uint8")

    # Display results
    st.image(colorized, channels="BGR", caption="Colorized Image")

    # Provide download link
    colorized_image = Image.fromarray(cv2.cvtColor(colorized, cv2.COLOR_BGR2RGB))
    colorized_image.save("colorized_output.jpg")
    with open("colorized_output.jpg", "rb") as file:
        btn = st.download_button(
            label="Download colorized image",
            data=file,
            file_name="colorized_image.jpg",
            mime="image/jpeg"
        )