from zoedepth.utils.geometry import depth_to_points, create_triangles import gradio as gr import spaces import numpy as np from PIL import Image import trimesh from functools import partial import tempfile def depth_edges_mask(depth): """Returns a mask of edges in the depth map. Args: depth: 2D numpy array of shape (H, W) with dtype float32. Returns: mask: 2D numpy array of shape (H, W) with dtype bool. """ # Compute the x and y gradients of the depth map. depth_dx, depth_dy = np.gradient(depth) # Compute the gradient magnitude. depth_grad = np.sqrt(depth_dx ** 2 + depth_dy ** 2) # Compute the edge mask. mask = depth_grad > 0.05 return mask def predict_depth(model, image): depth = model.infer_pil(image) return depth @spaces.GPU(enable_queue=True) def get_mesh(model, image: Image.Image, keep_edges=True): image.thumbnail((1024,1024)) # limit the size of the input image depth = predict_depth(model, image) pts3d = depth_to_points(depth[None]) pts3d = pts3d.reshape(-1, 3) # Create a trimesh mesh from the points # Each pixel is connected to its 4 neighbors # colors are the RGB values of the image verts = pts3d.reshape(-1, 3) image = np.array(image) if keep_edges: triangles = create_triangles(image.shape[0], image.shape[1]) else: triangles = create_triangles(image.shape[0], image.shape[1], mask=~depth_edges_mask(depth)) colors = image.reshape(-1, 3) mesh = trimesh.Trimesh(vertices=verts, faces=triangles, vertex_colors=colors) # Save as glb glb_file = tempfile.NamedTemporaryFile(suffix='.glb', delete=False) glb_path = glb_file.name mesh.export(glb_path) return glb_path def mesh_interface(model, device): with gr.Row(): with gr.Column(): inputs=[gr.Image(label="Input Image", type='pil'), gr.Checkbox(label="Keep occlusion edges", value=True)] outputs=gr.Model3D(label="3D Mesh", clear_color=[1.0, 1.0, 1.0, 1.0]) generate_btn = gr.Button(value="Generate") generate_btn.click(partial(get_mesh, model.to(device)), inputs=inputs, outputs=outputs, api_name="generate_mesh")