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| import gradio as gr | |
| from PIL import Image, ImageFilter | |
| import numpy as np | |
| import io | |
| import tempfile | |
| import vtracer | |
| from skimage import color, filters, feature, morphology | |
| import cv2 | |
| def preprocess_image(image, blur_radius, edge_enhance, edge_threshold, detail_level): | |
| """Preprocess the image with advanced options before vectorization.""" | |
| if blur_radius > 0: | |
| image = image.filter(ImageFilter.GaussianBlur(blur_radius)) | |
| # Convert to grayscale for edge detection | |
| gray_image = np.array(image.convert('L')) | |
| # Detail level settings | |
| if detail_level == 'Very Low': | |
| sigma = 3.0 | |
| morphology_size = 5 | |
| elif detail_level == 'Low': | |
| sigma = 2.0 | |
| morphology_size = 4 | |
| elif detail_level == 'Medium': | |
| sigma = 1.5 | |
| morphology_size = 3 | |
| elif detail_level == 'High': | |
| sigma = 1.0 | |
| morphology_size = 2 | |
| else: # Ultra | |
| sigma = 0.5 | |
| morphology_size = 1 | |
| if edge_enhance: | |
| # Canny edge detection | |
| edges = feature.canny(gray_image, sigma=sigma, low_threshold=edge_threshold) | |
| # Morphological operations to refine edges | |
| edges = morphology.dilation(edges, morphology.square(morphology_size)) | |
| edges_img = Image.fromarray((edges * 255).astype(np.uint8)) | |
| # Blend the edges with the original image | |
| image = Image.blend(image.convert('RGB'), edges_img.convert('RGB'), alpha=0.5) | |
| return image | |
| def convert_image(image, blur_radius, edge_enhance, edge_threshold, detail_level, color_mode, | |
| hierarchical, mode, filter_speckle, color_precision, layer_difference, | |
| corner_threshold, length_threshold, max_iterations, splice_threshold, path_precision): | |
| """Convert an image to SVG using vtracer with customizable and advanced parameters.""" | |
| # Preprocess the image with additional detail level settings | |
| image = preprocess_image(image, blur_radius, edge_enhance, edge_threshold, detail_level) | |
| # Convert Gradio image to bytes for vtracer compatibility | |
| img_byte_array = io.BytesIO() | |
| image.save(img_byte_array, format='PNG') | |
| img_bytes = img_byte_array.getvalue() | |
| # Perform the conversion | |
| svg_str = vtracer.convert_raw_image_to_svg( | |
| img_bytes, | |
| img_format='png', | |
| colormode=color_mode.lower(), | |
| hierarchical=hierarchical.lower(), | |
| mode=mode.lower(), | |
| filter_speckle=int(filter_speckle), | |
| color_precision=int(color_precision), | |
| layer_difference=int(layer_difference), | |
| corner_threshold=int(corner_threshold), | |
| length_threshold=float(length_threshold), | |
| max_iterations=int(max_iterations), | |
| splice_threshold=int(splice_threshold), | |
| path_precision=int(path_precision) | |
| ) | |
| # Save the SVG string to a temporary file | |
| temp_file = tempfile.NamedTemporaryFile(delete=False, suffix='.svg') | |
| temp_file.write(svg_str.encode('utf-8')) | |
| temp_file.close() | |
| # Display the SVG in the Gradio interface and provide the download link | |
| svg_html = f'<svg viewBox="0 0 {image.width} {image.height}">{svg_str}</svg>' | |
| return gr.HTML(svg_html), temp_file.name | |
| # Gradio interface | |
| iface = gr.Blocks() | |
| with iface: | |
| gr.Markdown("# Advanced Image to SVG Converter") | |
| gr.Markdown("Upload an image and customize the conversion parameters for high-quality vector results. This tool provides advanced options to analyze and vectorize images at a pixel level with various detail settings.") | |
| with gr.Row(): | |
| image_input = gr.Image(type="pil", label="Upload Image") | |
| blur_radius_input = gr.Slider(minimum=0, maximum=10, value=0, step=0.5, label="Blur Radius (for smoothing)") | |
| edge_enhance_input = gr.Checkbox(value=False, label="AI Edge Enhance") | |
| edge_threshold_input = gr.Slider(minimum=0.1, maximum=3.0, value=1.0, step=0.1, label="Edge Detection Threshold") | |
| detail_level_input = gr.Radio(choices=["Very Low", "Low", "Medium", "High", "Ultra"], value="Medium", label="Detail Level") | |
| with gr.Row(): | |
| color_mode_input = gr.Radio(choices=["Color", "Binary"], value="Color", label="Color Mode") | |
| hierarchical_input = gr.Radio(choices=["Stacked", "Cutout"], value="Stacked", label="Hierarchical") | |
| mode_input = gr.Radio(choices=["Spline", "Polygon", "None"], value="Spline", label="Mode") | |
| with gr.Row(): | |
| filter_speckle_input = gr.Slider(minimum=1, maximum=100, value=4, step=1, label="Filter Speckle") | |
| color_precision_input = gr.Slider(minimum=1, maximum=100, value=6, step=1, label="Color Precision") | |
| layer_difference_input = gr.Slider(minimum=1, maximum=100, value=16, step=1, label="Layer Difference") | |
| with gr.Row(): | |
| corner_threshold_input = gr.Slider(minimum=1, maximum=100, value=60, step=1, label="Corner Threshold") | |
| length_threshold_input = gr.Slider(minimum=1, maximum=100, value=4.0, step=0.5, label="Length Threshold") | |
| max_iterations_input = gr.Slider(minimum=1, maximum=100, value=10, step=1, label="Max Iterations") | |
| with gr.Row(): | |
| splice_threshold_input = gr.Slider(minimum=1, maximum=100, value=45, step=1, label="Splice Threshold") | |
| path_precision_input = gr.Slider(minimum=1, maximum=100, value=8, step=1, label="Path Precision") | |
| convert_button = gr.Button("Convert Image to SVG") | |
| svg_output = gr.HTML(label="SVG Output") | |
| download_output = gr.File(label="Download SVG") | |
| convert_button.click( | |
| fn=convert_image, | |
| inputs=[ | |
| image_input, blur_radius_input, edge_enhance_input, edge_threshold_input, detail_level_input, | |
| color_mode_input, hierarchical_input, mode_input, filter_speckle_input, color_precision_input, | |
| layer_difference_input, corner_threshold_input, length_threshold_input, max_iterations_input, | |
| splice_threshold_input, path_precision_input | |
| ], | |
| outputs=[svg_output, download_output] | |
| ) | |
| iface.launch() |