src/img2skt.py

import io
import os
import tempfile

import cv2
import gradio as gr
import numpy as np
from PIL import Image, ImageSequence


def image_to_sketch_gif(input_image: Image.Image):
    # Convert PIL image to OpenCV format
    open_cv_image = np.array(input_image.convert("RGB"))
    open_cv_image = cv2.cvtColor(open_cv_image, cv2.COLOR_RGB2BGR)

    # Convert to grayscale
    grayscale_image = cv2.cvtColor(open_cv_image, cv2.COLOR_BGR2GRAY)

    # Apply Gaussian blur
    blurred_image = cv2.GaussianBlur(grayscale_image, (5, 5), 0)

    # Use Canny Edge Detection
    edges = cv2.Canny(blurred_image, threshold1=50, threshold2=150)

    # Ensure binary format
    _, binary_sketch = cv2.threshold(edges, 128, 255, cv2.THRESH_BINARY)

    # Find connected components
    num_labels, labels, stats, _ = cv2.connectedComponentsWithStats(
        binary_sketch, connectivity=8
    )

    # Sort components by size (excluding the background, which is label 0)
    components = sorted(
        [(i, stats[i, cv2.CC_STAT_AREA]) for i in range(1, num_labels)],
        key=lambda x: x[1],
        reverse=True,
    )

    # Initialize an empty canvas for accumulation
    accumulated_image = np.zeros_like(binary_sketch, dtype=np.uint8)

    # Store frames
    frames = []

    for label, _ in components:
        # Add the current component to the accumulation
        accumulated_image[labels == label] = 255

        # Convert OpenCV image to PIL image and append to frames
        pil_frame = Image.fromarray(255 - accumulated_image)
        frames.append(pil_frame.copy())

    # Add the input_input as the final frame
    frames.append(input_image.copy())

    # Save GIF to a temporary file
    tmp_dir = tempfile.gettempdir()  # Get system temp directory
    tmp_gif_path = os.path.join(tmp_dir, "sketch_animation.gif")
    frames[0].save(
        tmp_gif_path,
        format="GIF",
        save_all=True,
        append_images=frames[1:],
        duration=100,
        loop=0,
    )

    return (
        tmp_gif_path,
        frames,
        gr.Slider(
            minimum=0,
            maximum=len(frames) - 1,
            value=0,
            step=1,
            visible=False,
            scale=4,
            label="Frame Selector",
            interactive=True,
        ),
        gr.Button("Stop", scale=1, visible=True),
    )