Update app.py

app.py

@@ -1,81 +1,67 @@
-
-import gradio as gr
-import vtracer
-import os
-import base64
-from io import BytesIO
-from PIL import Image
-import json
 from flask import Flask, request, jsonify
 from flask_cors import CORS
+from PIL import Image
+import vtracer
+import io
+import os
 
 app = Flask(__name__)
-CORS(app)
+CORS(app, resources={r"/convert-to-vector": {"origins": "*"}})
+
+def convert_to_vector(image):
+    input_path = "temp_input.png"
+    output_path = "svg_output.svg"
+
+    # Save input image
+    image.save(input_path)
 
-@app.route('/api/predict', methods=['POST'])
-def predict():
+    # Convert to SVG using VTracer
+    vtracer.convert_image_to_svg_py(
+        input_path,
+        output_path,
+        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
+    )
+
+    # Read SVG content
+    with open(output_path, "r") as f:
+        svg_content = f.read()
+
+    # Clean up
+    os.remove(input_path)
+    os.remove(output_path)
+
+    return svg_content
+
+@app.route('/convert-to-vector', methods=['POST'])
+def convert_to_vector_endpoint():
     try:
-        # Get image file from request
-        if 'image' not in request.files:
-            return jsonify({"error": "No image file provided"}), 400
-        
-        image_file = request.files['image']
-        image = Image.open(image_file)
-        
-        # Get parameters from request
-        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))
-        
-        # Create temp directory if it doesn't exist
-        os.makedirs('temp', exist_ok=True)
-        
-        # Save the input image to a temporary file
-        input_path = "temp/temp_input.jpg"
-        output_path = "temp/svg_output.svg"
-        
-        image.save(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=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
-        )
-        
-        # Read the SVG output
-        with open(output_path, "r") as f:
-            svg_content = f.read()
-        
-        # Create SVG with viewBox
-        full_svg = f'<svg viewBox="0 0 {image.width} {image.height}">{svg_content}</svg>'
-        
-        # Return SVG content and path
-        return jsonify({
-            "data": [full_svg, output_path],
-            "success": True
-        })
-    
+        if not request.data:
+            return jsonify({'error': 'No image data provided'}), 400
+
+        # Open image
+        image = Image.open(io.BytesIO(request.data)).convert('RGB')
+
+        # Convert to SVG
+        svg_content = convert_to_vector(image)
+
+        return svg_content, 200, {'Content-Type': 'text/plain'}
+
     except Exception as e:
-        return jsonify({"error": str(e), "success": False}), 500
+        return jsonify({'error': str(e)}), 500
+
+@app.route('/')
+def index():
+    return jsonify({'status': 'Image to Vector API is running'})
 
-if __name__ == "__main__":
-    app.run(host='0.0.0.0', port=7860)
+if __name__ == '__main__':
+    app.run(host='0.0.0.0', port=7860)