import numpy as np import trimesh import tempfile import torch from scipy.spatial import Delaunay from .build_pipe import * pipe = build_pipe() def generate_terrain(prompt, num_inference_steps, guidance_scale, seed, crop_size, prefix): """Generates terrain data (RGB and elevation) from a text prompt.""" if prefix and not prefix.endswith(' '): prefix += ' ' # Ensure prefix ends with a space full_prompt = prefix + prompt generator = torch.Generator("cuda").manual_seed(seed) image, dem = pipe(full_prompt, num_inference_steps=num_inference_steps, guidance_scale=guidance_scale, generator=generator) # Center crop the image and dem h, w, c = image[0].shape start_h = (h - crop_size) // 2 start_w = (w - crop_size) // 2 end_h = start_h + crop_size end_w = start_w + crop_size cropped_image = image[0][start_h:end_h, start_w:end_w, :] cropped_dem = dem[0][start_h:end_h, start_w:end_w, :] return (255 * cropped_image).astype(np.uint8), 500*cropped_dem.mean(-1) def simplify_mesh(mesh, target_face_count): """Simplifies a mesh using quadric decimation.""" simplified_mesh = mesh.simplify_quadric_decimation(target_face_count) return simplified_mesh def create_3d_mesh(rgb, elevation): """Creates a 3D mesh from RGB and elevation data.""" x, y = np.meshgrid(np.arange(elevation.shape[1]), np.arange(elevation.shape[0])) points = np.stack([x.flatten(), y.flatten()], axis=-1) tri = Delaunay(points) vertices = np.stack([x.flatten(), y.flatten(), elevation.flatten()], axis=-1) faces = tri.simplices mesh = trimesh.Trimesh(vertices=vertices, faces=faces, vertex_colors=rgb.reshape(-1, 3)) #mesh = simplify_mesh(mesh, target_face_count=100) return mesh def generate_and_display(prompt, num_inference_steps, guidance_scale, seed, crop_size, prefix): """Generates terrain and displays it as a 3D model.""" rgb, elevation = generate_terrain(prompt, num_inference_steps, guidance_scale, seed, crop_size, prefix) mesh = create_3d_mesh(rgb, elevation) with tempfile.NamedTemporaryFile(suffix=".obj", delete=False) as temp_file: mesh.export(temp_file.name) file_path = temp_file.name return file_path