Update app.py

app.py

@@ -1,68 +1,81 @@
-from flask import Flask, request, jsonify
-from flask_cors import CORS
-from PIL import Image
+
+import gradio as gr
 import vtracer
-import io
 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
 
 app = Flask(__name__)
-CORS(app, resources={r"/convert-to-vector": {"origins": "*"}})
-
-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"
-
-    # Save the input image to a temporary file
-    image.save(input_path)
+CORS(app)
 
-    # 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)
-    )
-
-    # Read the SVG output
-    with open(output_path, "r") as f:
-        svg_content = f.read()
-
-    # Clean up temporary files
-    os.remove(input_path)
-    os.remove(output_path)
-
-    return svg_content
-
-@app.route('/convert-to-vector', methods=['POST'])
-def convert_to_vector_endpoint():
+@app.route('/api/predict', methods=['POST'])
+def predict():
     try:
-        # Handle raw image data in the request body
-        if request.data:
-            image = Image.open(io.BytesIO(request.data)).convert('RGB')
-        else:
-            return jsonify({'error': 'No image data provided'}), 400
-
-        # Process the image
-        svg_content = convert_to_vector(image)
-
-        # Return the SVG content as plain text
-        return svg_content, 200, {'Content-Type': 'text/plain'}
-
+        # 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
+        })
+    
     except Exception as e:
-        return jsonify({'error': str(e)}), 500
-
-@app.route('/')
-def index():
-    return jsonify({'status': 'Image to Vector API is running'})
+        return jsonify({"error": str(e), "success": False}), 500
 
-if __name__ == '__main__':
-    app.run(host='0.0.0.0', port=7860)
+if __name__ == "__main__":
+    app.run(host='0.0.0.0', port=7860)