filters.py

import cv2
import numpy as np
from registry import registry

@registry.register("Original")
def original(image):
    return image

@registry.register("Grayscale")
def grayscale(image):
    return cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

@registry.register("Gaussian Blur", kernel_size=15)
def gaussian_blur(image, kernel_size: int = 15):
    return cv2.GaussianBlur(image, (kernel_size, kernel_size), 0)

@registry.register("Pencil Sketch")
def pencil_sketch(image):
    gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)
    inverted = cv2.bitwise_not(gray)
    blurred = cv2.GaussianBlur(inverted, (21, 21), 0)
    inverted_blurred = cv2.bitwise_not(blurred)
    return cv2.divide(gray, inverted_blurred, scale=256.0)

@registry.register("Sepia")
def sepia(image):
    kernel = np.array([
        [0.393, 0.769, 0.189],
        [0.349, 0.686, 0.168],
        [0.272, 0.534, 0.131]
    ])
    return cv2.transform(image, kernel)

@registry.register("Edge Enhance", intensity=1.5)
def edge_enhance(image, intensity: float = 1.5):
    kernel = np.array([
        [-1 * intensity, -1 * intensity, -1 * intensity],
        [-1 * intensity,  9 * intensity, -1 * intensity],
        [-1 * intensity, -1 * intensity, -1 * intensity]
    ])
    return cv2.filter2D(image, -1, kernel)

@registry.register("Adjust Contrast", alpha=1.5)
def adjust_contrast(image, alpha: float = 1.5):
    return cv2.convertScaleAbs(image, alpha=alpha, beta=0)