Render depth map and RGB image of ModelNet10 chair dataset from various view points

render_mesh_o3d.py

'''
Render depth map and RGB image of ModelNet10 chair dataset from various view points
'''

import open3d as o3d
import numpy as np
import json

NUM_VIEWS = 6

with open('front.json') as json_file:
	data = json.load(json_file)

train = open('debug_train.txt').readlines()
test = open('debug_test.txt').readlines()
all_files = train + test
all_files = ["ModelNet10/chair/train/" + f[:-1] + ".off" if f.endswith('\n') else "ModelNet10/chair/train/" + f + ".off" for f in all_files]

vis = o3d.visualization.Visualizer()
vis.create_window(visible=False)

for file in all_files:
	mesh = o3d.io.read_triangle_mesh(file)
	# subtract mean
	ver = np.asarray(mesh.vertices)
	for i, v in enumerate(ver):
		ver[i] = v - ver.mean(0)
	# normalize
	dist = [np.linalg.norm(v) for v in ver]
	ver = ver / max(dist)
	mesh.vertices = o3d.utility.Vector3dVector(ver)

	# sample points

	degrees = np.arange(0, 2*np.pi, np.pi/3)
	
	vis.add_geometry(mesh)

	for i in range(NUM_VIEWS):
		R = mesh.get_rotation_matrix_from_xyz((0, 0, 2 * np.pi / NUM_VIEWS))
		mesh.rotate(R, center=(0, 0, 0))
		
		# viewpoint set here
		ctr = vis.get_view_control()
		ctr.set_front(np.array(data['trajectory'][0]['front']))
		ctr.set_lookat(np.array(data['trajectory'][0]['lookat']))
		ctr.set_up(np.array(data['trajectory'][0]['up']))

		vis.update_geometry(mesh)
		vis.poll_events()
		vis.update_renderer()
		
		current_file = file[:-4] + "_" + str(i) + ".ply"
		vis.capture_depth_point_cloud(current_file, convert_to_world_coordinate=True)
		print(current_file)

	vis.remove_geometry(mesh)


vis.destroy_window()