FaceLift

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wlyu-adobe commited on Oct 13, 2025

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090676f

1 Parent(s): f563fa2

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app.py +2 -131

app.py CHANGED Viewed

@@ -47,9 +47,6 @@ from gslrm.model.gaussians_renderer import render_turntable, imageseq2video
 from mvdiffusion.pipelines.pipeline_mvdiffusion_unclip import StableUnCLIPImg2ImgPipeline
 from utils_folder.face_utils import preprocess_image, preprocess_image_without_cropping
-# Import convert function for PLY to SPLAT conversion
-import convert as ply_to_splat
 # HuggingFace repository configuration
 HF_REPO_ID = "wlyu/OpenFaceLift"
@@ -148,120 +145,6 @@ class FaceLiftPipeline:
             self._models_on_gpu = True
             print("Models on GPU, xformers enabled!")
-    def _create_viewer_html(self, splat_path):
-        """Create standalone HTML viewer for the gaussian splat."""
-        import base64
-        # Read the splat file and encode as base64
-        with open(splat_path, 'rb') as f:
-            splat_data = f.read()
-        splat_b64 = base64.b64encode(splat_data).decode('utf-8')
-        # Read the main.js content and modify it to use embedded data
-        with open(Path(__file__).parent / "main.js", 'r') as f:
-            js_content = f.read()
-        # Replace the URL fetching part with blob URL
-        js_content = js_content.replace(
-            'params.get("url") || "train.splat"',
-            'window.EMBEDDED_SPLAT_URL || "train.splat"'
-        )
-        html = f"""<!DOCTYPE html>
-<html lang="en">
-<head>
-    <meta charset="UTF-8">
-    <meta name="viewport" content="width=device-width, initial-scale=1.0">
-    <title>3D Gaussian Splat Viewer - FaceLift</title>
-    <style>
-        body {{
-            margin: 0;
-            padding: 0;
-            overflow: hidden;
-            font-family: Arial, sans-serif;
-            background: #000;
-        }}
-        #canvas {{
-            width: 100vw;
-            height: 100vh;
-            display: block;
-        }}
-        #info {{
-            position: absolute;
-            top: 10px;
-            left: 10px;
-            background: rgba(0, 0, 0, 0.7);
-            color: white;
-            padding: 10px;
-            border-radius: 5px;
-            font-size: 12px;
-            max-width: 300px;
-            z-index: 1000;
-        }}
-        #info h3 {{
-            margin: 0 0 10px 0;
-            font-size: 14px;
-        }}
-        #loading {{
-            position: absolute;
-            top: 50%;
-            left: 50%;
-            transform: translate(-50%, -50%);
-            color: white;
-            font-size: 18px;
-            text-align: center;
-            z-index: 999;
-        }}
-    </style>
-</head>
-<body>
-    <canvas id="canvas"></canvas>
-    <div id="loading">Loading 3D model...</div>
-    <div id="info">
-        <h3>Controls</h3>
-        <p><b>Mouse:</b> Click and drag to orbit</p>
-        <p><b>Right click/Ctrl+drag:</b> Move forward/back (up/down), strafe (left/right)</p>
-        <p><b>Arrow keys:</b> Move forward/back, strafe left/right</p>
-        <p><b>WASD:</b> Rotate camera</p>
-        <p><b>Space:</b> Jump</p>
-        <p><b>Q/E:</b> Roll camera</p>
-    </div>
-    <script>
-        // Convert base64 to blob and create URL
-        const SPLAT_DATA_B64 = '{splat_b64}';
-        function b64toBlob(b64Data, contentType='application/octet-stream', sliceSize=512) {{
-            const byteCharacters = atob(b64Data);
-            const byteArrays = [];
-            for (let offset = 0; offset < byteCharacters.length; offset += sliceSize) {{
-                const slice = byteCharacters.slice(offset, offset + sliceSize);
-                const byteNumbers = new Array(slice.length);
-                for (let i = 0; i < slice.length; i++) {{
-                    byteNumbers[i] = slice.charCodeAt(i);
-                }}
-                const byteArray = new Uint8Array(byteNumbers);
-                byteArrays.push(byteArray);
-            }}
-            return new Blob(byteArrays, {{type: contentType}});
-        }}
-        // Create blob URL for embedded splat data
-        const blob = b64toBlob(SPLAT_DATA_B64);
-        window.EMBEDDED_SPLAT_URL = URL.createObjectURL(blob);
-        // Remove loading message once render starts
-        setTimeout(() => {{
-            const loading = document.getElementById('loading');
-            if (loading) loading.style.display = 'none';
-        }}, 2000);
-    </script>
-    <script>
-        {js_content}
-    </script>
-</body>
-</html>"""
-        return html
     @spaces.GPU
     def generate_3d_head(self, image_path, auto_crop=True, guidance_scale=3.0,
                          random_seed=4, num_steps=50):
@@ -358,16 +241,6 @@ class FaceLiftPipeline:
             ply_path = output_dir / "gaussians.ply"
             filtered_gaussians.save_ply(str(ply_path))
-            # Convert PLY to SPLAT format for web viewer
-            splat_path = output_dir / "gaussians.splat"
-            ply_to_splat.convert(str(ply_path), str(splat_path))
-            # Create HTML viewer
-            viewer_html = self._create_viewer_html(str(splat_path))
-            viewer_path = output_dir / "viewer.html"
-            with open(viewer_path, 'w') as f:
-                f.write(viewer_html)
             # Save output image
             comp_image = rearrange(comp_image, "x v c h w -> (x h) (v w) c")
             comp_image = (comp_image.cpu().numpy() * 255.0).clip(0, 255).astype(np.uint8)
@@ -384,7 +257,7 @@ class FaceLiftPipeline:
             imageseq2video(turntable_frames, str(turntable_path), fps=30)
             return str(input_path), str(multiview_path), str(output_path), \
-                   str(turntable_path), str(viewer_path), str(ply_path)
         except Exception as e:
             raise gr.Error(f"Generation failed: {str(e)}")
@@ -405,12 +278,11 @@ def main():
         fn=pipeline.generate_3d_head,
         title="FaceLift: Single Image 3D Face Reconstruction",
         description="""
-        Transform a single portrait image into a complete 3D head model with an interactive WebGL viewer.
         **Tips:**
         - Use high-quality portrait images with clear facial features
         - If face detection fails, try disabling auto-cropping and manually crop to square
-        - Download the Interactive 3D Viewer HTML file to explore your model in full screen
         """,
         inputs=[
             gr.Image(type="filepath", label="Input Portrait Image"),
@@ -424,7 +296,6 @@ def main():
             gr.Image(label="Multi-view Generation"),
             gr.Image(label="3D Reconstruction"),
             gr.PlayableVideo(label="Turntable Animation"),
-            gr.File(label="Interactive 3D Viewer (.html) - Download & Open"),
             gr.File(label="3D Model (.ply)"),
         ],
         examples=examples,

 from mvdiffusion.pipelines.pipeline_mvdiffusion_unclip import StableUnCLIPImg2ImgPipeline
 from utils_folder.face_utils import preprocess_image, preprocess_image_without_cropping
 # HuggingFace repository configuration
 HF_REPO_ID = "wlyu/OpenFaceLift"
             self._models_on_gpu = True
             print("Models on GPU, xformers enabled!")
     @spaces.GPU
     def generate_3d_head(self, image_path, auto_crop=True, guidance_scale=3.0,
                          random_seed=4, num_steps=50):
             ply_path = output_dir / "gaussians.ply"
             filtered_gaussians.save_ply(str(ply_path))
             # Save output image
             comp_image = rearrange(comp_image, "x v c h w -> (x h) (v w) c")
             comp_image = (comp_image.cpu().numpy() * 255.0).clip(0, 255).astype(np.uint8)
             imageseq2video(turntable_frames, str(turntable_path), fps=30)
             return str(input_path), str(multiview_path), str(output_path), \
+                   str(turntable_path), str(ply_path)
         except Exception as e:
             raise gr.Error(f"Generation failed: {str(e)}")
         fn=pipeline.generate_3d_head,
         title="FaceLift: Single Image 3D Face Reconstruction",
         description="""
+        Transform a single portrait image into a complete 3D head model.
         **Tips:**
         - Use high-quality portrait images with clear facial features
         - If face detection fails, try disabling auto-cropping and manually crop to square
         """,
         inputs=[
             gr.Image(type="filepath", label="Input Portrait Image"),
             gr.Image(label="Multi-view Generation"),
             gr.Image(label="3D Reconstruction"),
             gr.PlayableVideo(label="Turntable Animation"),
             gr.File(label="3D Model (.ply)"),
         ],
         examples=examples,