Update app.py

app.py

@@ -1,11 +1,16 @@
 import gradio as gr
 import vtracer
 import os
-from fastapi import FastAPI, File, UploadFile, Form
+from fastapi import FastAPI, File, UploadFile, Form, HTTPException
 from fastapi.responses import JSONResponse
 from fastapi.middleware.cors import CORSMiddleware
 from PIL import Image
 import io
+import logging
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
 
 # Initialize FastAPI app
 app = FastAPI()
@@ -13,7 +18,7 @@ app = FastAPI()
 # Configure CORS to allow requests from Figma plugin
 app.add_middleware(
     CORSMiddleware,
-    allow_origins=["https://www.figma.com"],  # Restrict to Figma's domain
+    allow_origins=["https://www.figma.com"],
     allow_credentials=True,
     allow_methods=["*"],
     allow_headers=["*"],
@@ -37,35 +42,43 @@ def convert_to_vector(
     input_path = "temp_input.jpg"
     output_path = "svg_output.svg"
 
-    # Save the input image to a temporary file
-    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=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)
-    )
+    try:
+        # Save the input image to a temporary file
+        image.save(input_path)
 
-    # Read the SVG output
-    with open(output_path, "r") as f:
-        svg_content = f.read()
+        # 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)
+        )
 
-    # Clean up temporary files
-    os.remove(input_path)
-    os.remove(output_path)
+        # Read the SVG output
+        with open(output_path, "r") as f:
+            svg_content = f.read()
 
-    return svg_content
+        return svg_content
+    # except Exception as e:
+    #     logger.error(f"Error in convert_to_vector: {str(e)}")
+    #     raise HTTPException(status_code=500, detail=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)
+                except Exception as e:
+                    logger.warning(f"Failed to remove {path}: {str(e)}")
 
 # FastAPI endpoint for vector conversion
 @app.post("/convert")
@@ -106,14 +119,147 @@ async def convert_image(
 
         return JSONResponse(content={"svg": svg_content})
     except Exception as e:
+        logger.error(f"Error in convert_image: {str(e)}")
         return JSONResponse(content={"error": str(e)}, status_code=500)
 
-# Existing Gradio interface (unchanged)
-with gr.Blocks(css=...) as gradio_app:
-    # Your existing Gradio code here (omitted for brevity)
-    pass
+# Gradio interface
+def handle_color_mode(value):
+    return value
+
+examples = [
+    "examples/11.jpg",
+    "examples/02.jpg",
+    "examples/03.jpg",
+]
+
+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);
+}
+"""
+
+# Define the Gradio interface
+with gr.Blocks(css=css) as gradio_app:
+    with gr.Column(elem_id="col-container"):
+        gr.HTML("""
+                <div style="text-align: center;">
+                    <h2>Image to Vector Converter ⚡</h2>
+                    <p>Converts raster images (JPG, PNG, WEBP) to vector graphics (SVG).</p>
+                </div>
+            """)
+        with gr.Row():
+            with gr.Column():
+                image_input = gr.Image(type="pil", label="Upload Image")
+                with gr.Accordion("Advanced Settings", open=False):
+                    with gr.Accordion("Clustering", open=False):
+                        colormode = gr.Radio([("COLOR","color"),("B/W", "binary")], value="color", label="Color Mode", show_label=False)
+                        filter_speckle = gr.Slider(0, 128, value=4, step=1, label="Filter Speckle", info="Cleaner")
+                        color_precision = gr.Slider(1, 8, value=6, step=1, label="Color Precision", info="More accurate")
+                        layer_difference = gr.Slider(0, 128, value=16, step=1, label="Gradient Step", info="Less layers")
+                        hierarchical = gr.Radio([("STACKED","stacked"), ("CUTOUT","cutout")], value="stacked", label="Hierarchical Mode",show_label=False)
+                    with gr.Accordion("Curve Fitting", open=False):
+                        mode = gr.Radio([("SPLINE","spline"),("POLYGON", "polygon"), ("PIXEL","none")], value="spline", label="Mode", show_label=False)
+                        corner_threshold = gr.Slider(0, 180, value=60, step=1, label="Corner Threshold", info="Smoother")
+                        length_threshold = gr.Slider(3.5, 10, value=4.0, step=0.1, label="Segment Length", info ="More coarse")
+                        splice_threshold = gr.Slider(0, 180, value=45, step=1, label="Splice Threshold", info="Less accurate")
+                        max_iterations = gr.Slider(1, 20, value=10, step=1, label="Max Iterations", visible=False)
+                        path_precision = gr.Slider(1, 10, value=3, step=1, label="Path Precision", visible=False)
+                        output_text = gr.Textbox(label="Selected Mode", visible=False)
+                with gr.Row():
+                    clear_button = gr.Button("Clear")
+                    convert_button = gr.Button("✨ Convert to SVG", variant='primary', elem_classes=["generate-btn"])
+
+            with gr.Column():
+                html = gr.HTML(label="SVG Output")
+                svg_output = gr.File(label="Download SVG")
+        
+        gr.Examples(
+            examples=examples,
+            fn=convert_to_vector,
+            inputs=[image_input],
+            outputs=[html, svg_output],
+            cache_examples=False,
+            run_on_click=True
+        )
+
+    colormode.change(handle_color_mode, inputs=colormode, outputs=output_text)
+    hierarchical.change(handle_color_mode, inputs=hierarchical, outputs=output_text)
+    mode.change(handle_color_mode, inputs=mode, outputs=output_text)
+    default_values = {
+        "color_precision": 6,
+        "layer_difference": 16
+    }
+
+    def clear_inputs():
+        return (
+            gr.Image(value=None), gr.Radio(value="color"), gr.Radio(value="stacked"),
+            gr.Radio(value="spline"), gr.Slider(value=4), gr.Slider(value=6),
+            gr.Slider(value=16), gr.Slider(value=60), gr.Slider(value=4.0),
+            gr.Slider(value=10), gr.Slider(value=45), gr.Slider(value=3)
+        )
+
+    def update_interactivity_and_visibility(colormode, color_precision_value, layer_difference_value):
+        is_color_mode = colormode == "color"
+        return (
+            gr.update(interactive=is_color_mode),
+            gr.update(interactive=is_color_mode),
+            gr.update(visible=is_color_mode)
+        )
+
+    colormode.change(
+        update_interactivity_and_visibility,
+        inputs=[colormode, color_precision, layer_difference],
+        outputs=[color_precision, layer_difference, hierarchical]
+    )
+
+    def update_interactivity_and_visibility_for_mode(mode):
+        is_spline_mode = mode == "spline"
+        return (
+            gr.update(interactive=is_spline_mode),
+            gr.update(interactive=is_spline_mode),
+            gr.update(interactive=is_spline_mode)
+        )
+
+    mode.change(
+        update_interactivity_and_visibility_for_mode,
+        inputs=[mode],
+        outputs=[corner_threshold, length_threshold, splice_threshold]
+    )
+
+    clear_button.click(
+        clear_inputs,
+        outputs=[
+            image_input, colormode, hierarchical, mode, filter_speckle,
+            color_precision, layer_difference, corner_threshold, length_threshold,
+            max_iterations, splice_threshold, path_precision
+        ]
+    )
+
+    convert_button.click(
+        convert_to_vector,
+        inputs=[
+            image_input, colormode, hierarchical, mode, filter_speckle,
+            color_precision, layer_difference, corner_threshold, length_threshold,
+            max_iterations, splice_threshold, path_precision
+        ],
+        outputs=[html, svg_output]
+    )
 
-# Mount Gradio app to FastAPI
-app.mount("/", gradio_app)
+# Mount Gradio app to FastAPI at a subpath
+from gradio import mount_gradio_app
+app = mount_gradio_app(app, gradio_app, path="/gradio")
 
-# Note: app.launch() is not needed for Hugging Face Spaces; it will be handled by the platform
+# Health check endpoint
+@app.get("/")
+async def health_check():
+    return {"status": "healthy"}