Spaces:
Sleeping
Sleeping
import gradio as gr | |
import numpy as np | |
import trimesh | |
from geometry import depth_to_points, create_triangles | |
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, keep_edges=False): | |
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 create_demo(model): | |
gr.Markdown("### Image to 3D mesh") | |
gr.Markdown("Convert a single 2D image to a 3D mesh") | |
with gr.Row(): | |
image = gr.Image(label="Input Image", type='pil') | |
result = gr.Model3D(label="3d mesh reconstruction", clear_color=[ | |
1.0, 1.0, 1.0, 1.0]) | |
checkbox = gr.Checkbox(label="Keep occlusion edges", value=False) | |
submit = gr.Button("Submit") | |
submit.click(partial(get_mesh, model), inputs=[image, checkbox], outputs=[result]) | |
examples = gr.Examples(examples=["examples/aerial_beach.jpeg", "examples/mountains.jpeg", "examples/person_1.jpeg", "examples/ancient-carved.jpeg"], | |
inputs=[image]) | |