app.py

import streamlit as st
import numpy as np
import cv2
import matplotlib.pyplot as plt
from sklearn.cluster import KMeans
from io import BytesIO

# Function to extract dominant colors
def extract_colors(image, num_colors):
    image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
    pixels = image.reshape(-1, 3)  # Reshape to 2D array
    
    kmeans = KMeans(n_clusters=num_colors, n_init=10, random_state=42)
    kmeans.fit(pixels)
    
    colors = kmeans.cluster_centers_.astype(int)
    return colors

# Function to display the color palette
def display_palette(colors):
    fig, ax = plt.subplots(figsize=(8, 2))
    ax.imshow([colors], aspect='auto')
    ax.set_xticks([])
    ax.set_yticks([])
    st.pyplot(fig)

# Streamlit UI Design
st.set_page_config(page_title="Color Palette Generator", page_icon="🎨", layout="centered")

# Custom CSS for aesthetics
st.markdown(
    """
    <style>
        .title {
            text-align: center;
            font-size: 36px;
            font-weight: bold;
            color: #4A90E2;
        }
        .subtitle {
            text-align: center;
            font-size: 20px;
            color: #7F8C8D;
        }
        .uploaded-img {
            display: flex;
            justify-content: center;
        }
    </style>
    """,
    unsafe_allow_html=True,
)

# Header Design
st.markdown("<div class='title'>🎨 K-Means Color Palette Generator</div>", unsafe_allow_html=True)
st.markdown("<div class='subtitle'>Upload an image and extract its dominant colors!</div>", unsafe_allow_html=True)

uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
num_colors = st.slider("Select Number of Colors", 2, 10, 5)

if uploaded_file is not None:
    file_bytes = np.asarray(bytearray(uploaded_file.read()), dtype=np.uint8)
    image = cv2.imdecode(file_bytes, cv2.IMREAD_COLOR)
    
    st.markdown("<div class='uploaded-img'>", unsafe_allow_html=True)
    st.image(cv2.cvtColor(image, cv2.COLOR_BGR2RGB), caption="Uploaded Image", use_column_width=True)
    st.markdown("</div>", unsafe_allow_html=True)
    
    colors = extract_colors(image, num_colors)
    
    st.write("## 🎨 Extracted Color Palette")
    display_palette(colors)
    
    # Show color RGB values
    st.write("## 🌈 RGB Values of Extracted Colors")
    color_columns = st.columns(num_colors)
    for i, color in enumerate(colors):
        with color_columns[i]:
            st.markdown(f"""<div style='background-color: rgb({color[0]}, {color[1]}, {color[2]}); 
                                  height: 50px; border-radius: 10px;'></div>""", unsafe_allow_html=True)
            st.write(f"RGB({color[0]}, {color[1]}, {color[2]})")