Update app.py

app.py

@@ -72,6 +72,101 @@ class PersistentCortex:
         self.colors = torch.clamp(self.colors + color_shift.repeat(self.num, 1) * 0.3, 0, 1)
         return self
 
+    def export_ply(self, path="output.ply"):
+        # Prepare vertex data matching gsplat.js expected properties
+        zeros = np.zeros((self.num, 3), dtype=np.float32)
+        log_scales = np.log(self.scales.cpu().numpy()).astype(np.float32)
+
+        vertex_data = np.core.records.fromarrays([
+            self.positions.cpu().numpy().astype(np.float32).T,
+            zeros.T,  # normals (unused)
+            self.colors.cpu().numpy().T,
+            self.opacities.cpu().numpy().reshape(1, -1).T,
+            log_scales.T,
+            self.rotations.cpu().numpy().T
+        ], names='x,y,z,nx,ny,nz,f_dc_0,f_dc_1,f_dc_2,opacity,scale_0,scale_1,scale_2,rot_0,rot_1,rot_2,rot_3')
+
+        el = plyfile.PlyElement.describe(vertex_data, 'vertex')
+        plyfile.PlyData([el], text=True).write(path)
+        return os.path.abspath(path)
+
+def process(image: Image.Image, prompt: str = ""):
+    if image is None:
+        raise ValueError("Please upload an image to proceed.")
+    
+    cortex = PersistentCortex(num_gaussians=8000)
+    cortex.evolve_from_image(image, steps=800)
+    if prompt:
+        cortex.condition_on_prompt(prompt)
+
+    ply_path = cortex.export_ply("/tmp/output.ply")
+
+    # In Hugging Face Spaces, /tmp files are automatically served under /files/
+    viewer_html = f"""
+    <div id="viewer" style="width:100%; height:600px; background:#000;"></div>
+    <script type="module">
+    import * as SPLAT from "https://cdn.jsdelivr.net/npm/gsplat@latest";
+
+    const container = document.getElementById('viewer');
+    const canvas = document.createElement('canvas');
+    canvas.style.width = '100%';
+    canvas.style.height = '100%';
+    container.appendChild(canvas);
+
+    const scene = new SPLAT.Scene();
+    const camera = new SPLAT.Camera();
+    const renderer = new SPLAT.WebGLRenderer({{ canvas }});
+    const controls = new SPLAT.OrbitControls(camera, canvas);
+
+    controls.autoRotate = false;
+    controls.enableDamping = true;
+    controls.dampingFactor = 0.05;
+    controls.rotateSpeed = 1.0;
+    controls.zoomSpeed = 1.2;
+    controls.panSpeed = 0.8;
+
+    await SPLAT.Loader.LoadAsync("/files/output.ply", scene);
+
+    function animate() {{
+        controls.update();
+        renderer.render(scene, camera);
+        requestAnimationFrame(animate);
+    }}
+    animate();
+    </script>
+    """
+
+    status = "3D Gaussian splat generated and evolved from your image"
+    if prompt:
+        status += f" with prompt conditioning: '{prompt}'."
+    else:
+        status += "."
+
+    return viewer_html, status
+
+with gr.Blocks(title="Persistent 3D Cortex Demo") as demo:
+    gr.Markdown("# Persistent 3D Cortex – Interactive Demo")
+    gr.Markdown("""
+    Upload an image and optionally add a text prompt.  
+    The system evolves a persistent 3D Gaussian splat representation influenced by the image content and prompt.
+    """)
+    
+    with gr.Row():
+        img_input = gr.Image(type="pil", label="Input Image")
+        prompt_input = gr.Textbox(label="Prompt (e.g., 'shiny red apple', 'futuristic city')", placeholder="Optional text prompt")
+    
+    generate_btn = gr.Button("Generate & Evolve 3D", variant="primary")
+    
+    viewer_output = gr.HTML(label="Interactive 3D Viewer")
+    status_output = gr.Textbox(label="Status")
+
+    generate_btn.click(
+        fn=process,
+        inputs=[img_input, prompt_input],
+        outputs=[viewer_output, status_output]
+    )
+
+demo.launch()
     def export_ply(self, path="output.ply"):
         # Prepare vertex data matching gsplat.js expected properties
         zeros = np.zeros((self.num, 3), dtype=np.float32)