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| import gradio as gr | |
| import cv2 | |
| import numpy as np | |
| class ImageToSketchEffect: | |
| """Transform an image to mimic the effect of a sketch drawn with a pencil.""" | |
| def __init__( | |
| self, | |
| blur_strength: int = 5, | |
| blur_kernel_size: tuple = (0, 0), | |
| edge_enhance_level: int = None, | |
| custom_sharpen_kernel: np.ndarray = None, | |
| ): | |
| self.blur_strength = blur_strength | |
| self.blur_kernel_size = blur_kernel_size | |
| self.edge_enhance_level = edge_enhance_level | |
| self.sharpen_kernel = np.array([[0, -1, 0], [-1, edge_enhance_level, -1], | |
| [0, -1, 0]]) if custom_sharpen_kernel is None else custom_sharpen_kernel | |
| def blend_mode_dodge(self, top_layer: np.ndarray, bottom_layer: np.ndarray) -> np.ndarray: | |
| output = bottom_layer * 255.0 / (255.0 - top_layer) | |
| output[output > 255] = 255 | |
| output[bottom_layer == 255] = 255 | |
| return output.astype('uint8') | |
| def enhance_edges(self, img: np.ndarray) -> np.ndarray: | |
| if self.edge_enhance_level is not None and isinstance(self.edge_enhance_level, int): | |
| inverse_image = 255 - img | |
| return 255 - cv2.filter2D(src=inverse_image, ddepth=-1, kernel=self.sharpen_kernel) | |
| return img | |
| def apply_sketch_effect(self, image: np.ndarray) -> (np.ndarray, np.ndarray): | |
| grayscale_image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) | |
| inverted_image = 255 - grayscale_image | |
| blurred_image = cv2.GaussianBlur(inverted_image, ksize=self.blur_kernel_size, sigmaX=self.blur_strength) | |
| sketch_image = self.blend_mode_dodge(blurred_image, grayscale_image) | |
| sketch_image = self.enhance_edges(sketch_image) | |
| blurred_for_alpha = cv2.GaussianBlur(sketch_image, (5, 5), 0) | |
| if len(blurred_for_alpha.shape) == 3 and blurred_for_alpha.shape[2] == 3: | |
| blurred_for_alpha = cv2.cvtColor(blurred_for_alpha, cv2.COLOR_BGR2GRAY) | |
| _, alpha_mask = cv2.threshold(blurred_for_alpha, 0, 255, cv2.THRESH_BINARY_INV + cv2.THRESH_OTSU) | |
| final_sketch_transparent = cv2.merge((blurred_for_alpha, blurred_for_alpha, blurred_for_alpha, alpha_mask)) | |
| return sketch_image, final_sketch_transparent | |
| def process_image(image, blur_strength, blur_kernel_size, edge_enhance_level): | |
| sketch_effect = ImageToSketchEffect(blur_strength, (blur_kernel_size, blur_kernel_size), edge_enhance_level) | |
| return sketch_effect.apply_sketch_effect(image) | |
| iface = gr.Interface(fn=process_image, | |
| inputs=[gr.Image(), gr.Slider(1, 10, value=7), gr.Slider(3, 25, step=2, value=15), | |
| gr.Slider(1, 10, value=7)], | |
| outputs=[gr.Image(type="numpy", label="Pencil Sketch"),gr.Image(type="numpy", label="Transparent Pencil Sketch")], | |
| title="Image to Sketch Converter", | |
| description="Upload an image to convert it into a pencil sketch.") | |
| if __name__ == "__main__": | |
| iface.launch() | |