from flask import Flask, request, jsonify, send_file from flask_cors import CORS import vtracer from PIL import Image import io import os import logging import gradio as gr # Set up logging logging.basicConfig(level=logging.INFO) logger = logging.getLogger(__name__) app = Flask(__name__) CORS(app, resources={r"/convert": {"origins": ["https://www.figma.com", "*"]}}) # VTracer conversion function def convert_to_vector( image, colormode="color", hierarchical="stacked", mode="spline", filter_speckle=4, color_precision=6, layer_difference=16, corner_threshold=60, length_threshold=4.0, max_iterations=10, splice_threshold=45, path_precision=3 ): input_path = "temp_input.jpg" output_path = "svg_output.svg" try: # Save the input image to a temporary file image.save(input_path) logger.info(f"Saved image to {input_path}") # Convert the image to SVG using VTracer vtracer.convert_image_to_svg_py( input_path, output_path, colormode=colormode, hierarchical=hierarchical, mode=mode, 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) ) logger.info(f"Converted image to SVG at {output_path}") # Read the SVG output with open(output_path, "r") as f: svg_content = f.read() return svg_content except Exception as e: logger.error(f"Error in convert_to_vector: {str(e)}") raise Exception(f"Conversion failed: {str(e)}") finally: # Clean up temporary files for path in [input_path, output_path]: if os.path.exists(path): try: os.remove(path) logger.info(f"Removed {path}") except Exception as e: logger.warning(f"Failed to remove {path}: {str(e)}") # Flask endpoint for vector conversion @app.route('/convert', methods=['POST']) def convert_image(): try: # Handle image upload if 'file' not in request.files: return jsonify({'error': 'No image file provided'}), 400 file = request.files['file'] image = Image.open(file).convert('RGB') # Get parameters (with defaults) colormode = request.form.get('colormode', 'color') hierarchical = request.form.get('hierarchical', 'stacked') mode = request.form.get('mode', 'spline') filter_speckle = int(request.form.get('filter_speckle', 4)) color_precision = int(request.form.get('color_precision', 6)) layer_difference = int(request.form.get('layer_difference', 16)) corner_threshold = int(request.form.get('corner_threshold', 60)) length_threshold = float(request.form.get('length_threshold', 4.0)) max_iterations = int(request.form.get('max_iterations', 10)) splice_threshold = int(request.form.get('splice_threshold', 45)) path_precision = int(request.form.get('path_precision', 3)) logger.info("Received request to /convert") # Convert to SVG svg_content = convert_to_vector( image, colormode=colormode, hierarchical=hierarchical, mode=mode, filter_speckle=filter_speckle, color_precision=color_precision, layer_difference=layer_difference, corner_threshold=corner_threshold, length_threshold=length_threshold, max_iterations=max_iterations, splice_threshold=splice_threshold, path_precision=path_precision ) # Return SVG as JSON return jsonify({'svg': svg_content}) except Exception as e: logger.error(f"Error in convert_image: {str(e)}") return jsonify({'error': str(e)}), 500 # Health check endpoint @app.route('/') def health_check(): logger.info("Health check requested") return jsonify({'status': 'Image to Vector Converter API is running'}) # Optional Gradio interface (comment out if not needed) def handle_color_mode(value): return value examples_dir = "examples" examples = [ os.path.join(examples_dir, f) for f in ["11.jpg", "02.jpg", "03.jpg"] if os.path.exists(os.path.join(examples_dir, f)) ] css = """ #col-container { margin: 0 auto; max-width: 960px; } .generate-btn { background: linear-gradient(90deg, #4B79A1 0%, #283E51 100%) !important; border: none !important; color: white !important; } .generate-btn:hover { transform: translateY(-2px); box-shadow: 0 5px 15px rgba(0,0,0,0.2); } """ with gr.Blocks(css=css) as gradio_app: with gr.Column(elem_id="col-container"): gr.HTML("""
Converts raster images (JPG, PNG, WEBP) to vector graphics (SVG).