mesh.py

from zoedepth.utils.geometry import depth_to_points, create_triangles
import gradio as gr
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

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):
    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")