import numpy as np

import cv2

import os

# Path to the uploaded image

image_path = "/mnt/data/404614311_891495322548092_4664051338560382022_n.webp"

# Load the image

image = cv2.imread(image_path)

# Resize for faster processing

image_small = cv2.resize(image, (200, 200))

# Convert to LAB for better color clustering

image_lab = cv2.cvtColor(image_small, cv2.COLOR_BGR2LAB)

pixels = image_lab.reshape((-1, 3))

# KMeans to extract main colors

from sklearn.cluster import KMeans

kmeans = KMeans(n_clusters=6, random_state=42).fit(pixels)

colors = kmeans.cluster_centers_.astype(int)

# Convert colors back to RGB

colors_rgb = cv2.cvtColor(np.array([colors], dtype=np.uint8), cv2.COLOR_Lab2BGR)[0]

colors_rgb_list = colors_rgb.tolist()

colors_rgb_list