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import gradio as gr |
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import numpy as np |
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import trimesh |
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from geometry import depth_to_points, create_triangles |
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from functools import partial |
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import tempfile |
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def depth_edges_mask(depth): |
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"""Returns a mask of edges in the depth map. |
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Args: |
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depth: 2D numpy array of shape (H, W) with dtype float32. |
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Returns: |
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mask: 2D numpy array of shape (H, W) with dtype bool. |
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""" |
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depth_dx, depth_dy = np.gradient(depth) |
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depth_grad = np.sqrt(depth_dx ** 2 + depth_dy ** 2) |
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mask = depth_grad > 0.05 |
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return mask |
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def predict_depth(model, image): |
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depth = model.infer_pil(image) |
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return depth |
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def get_mesh(model, image, keep_edges=False): |
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image.thumbnail((1024,1024)) |
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depth = predict_depth(model, image) |
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pts3d = depth_to_points(depth[None]) |
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pts3d = pts3d.reshape(-1, 3) |
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verts = pts3d.reshape(-1, 3) |
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image = np.array(image) |
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if keep_edges: |
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triangles = create_triangles(image.shape[0], image.shape[1]) |
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else: |
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triangles = create_triangles(image.shape[0], image.shape[1], mask=~depth_edges_mask(depth)) |
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colors = image.reshape(-1, 3) |
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mesh = trimesh.Trimesh(vertices=verts, faces=triangles, vertex_colors=colors) |
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glb_file = tempfile.NamedTemporaryFile(suffix='.glb', delete=False) |
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glb_path = glb_file.name |
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mesh.export(glb_path) |
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return glb_path |
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def create_demo(model): |
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gr.Markdown("### Image to 3D mesh") |
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gr.Markdown("Convert a single 2D image to a 3D mesh") |
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with gr.Row(): |
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image = gr.Image(label="Input Image", type='pil') |
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result = gr.Model3D(label="3d mesh reconstruction", clear_color=[ |
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1.0, 1.0, 1.0, 1.0]) |
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checkbox = gr.Checkbox(label="Keep occlusion edges", value=False) |
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submit = gr.Button("Submit") |
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submit.click(partial(get_mesh, model), inputs=[image, checkbox], outputs=[result]) |
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examples = gr.Examples(examples=["examples/aerial_beach.jpeg", "examples/00000-2244071438.png", "examples/person_1.jpeg", "examples/ancient-carved.jpeg"], |
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inputs=[image]) |
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