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object_renderer.py
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object_renderer.py
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# Copyright (c) 2019, NVIDIA CORPORATION. All rights reserved.
#
# NVIDIA CORPORATION and its licensors retain all intellectual property
# and proprietary rights in and to this software, related documentation
# and any modifications thereto. Any use, reproduction, disclosure or
# distribution of this software and related documentation without an express
# license agreement from NVIDIA CORPORATION is strictly prohibited.
from __future__ import print_function
from __future__ import absolute_import
import trimesh
import trimesh.transformations as tra
import pyrender
import numpy as np
import copy
import cv2
import h5py
import sample
import math
import sys
import argparse
import os
class ObjectRenderer:
def __init__(self, fov=np.pi / 6, object_paths=[], object_scales=[]):
"""
Args:
fov: float,
"""
self._fov = fov
self.mesh = None
self._scene = None
self.tmesh = None
self._init_scene()
self._object_nodes = []
self._object_means = []
self._object_distances = []
assert(isinstance(object_paths, list))
assert(len(object_paths) > 0)
for path, scale in zip(object_paths, object_scales):
node, obj_mean = self._load_object(path, scale)
self._object_nodes.append(node)
self._object_means.append(obj_mean)
def _init_scene(self):
self._scene = pyrender.Scene()
camera = pyrender.PerspectiveCamera(yfov=self._fov, aspectRatio=1.0, znear=0.001) # do not change aspect ratio
camera_pose = tra.euler_matrix(np.pi, 0, 0)
self._scene.add(camera, pose=camera_pose, name='camera')
light = pyrender.SpotLight(color=np.ones(4), intensity=3., innerConeAngle=np.pi/16, outerConeAngle=np.pi/6.0)
self._scene.add(light, pose=camera_pose, name='light')
self.renderer = pyrender.OffscreenRenderer(400, 400)
def _load_object(self, path, scale=1.0):
obj = sample.Object(path)
obj.rescale(scale)
print('rescaling with scale', scale)
tmesh = obj.mesh
tmesh_mean = np.mean(tmesh.vertices, 0)
tmesh.vertices -= np.expand_dims(tmesh_mean, 0)
lbs = np.min(tmesh.vertices, 0)
ubs = np.max(tmesh.vertices, 0)
self._object_distances.append(np.max(ubs - lbs) * 5)
print(self._object_distances)
self.tmesh = copy.deepcopy(tmesh)
mesh = pyrender.Mesh.from_trimesh(tmesh)
return self._scene.add(mesh, name='object'), np.expand_dims(tmesh_mean, 0)
def _to_pointcloud(self, depth):
fy = fx = 0.5 / np.tan(self._fov * 0.5) # aspectRatio is one.
height = depth.shape[0]
width = depth.shape[1]
mask = np.where(depth > 0)
x = mask[1]
y = mask[0]
normalized_x = (x.astype(np.float32) - width * 0.5) / width
normalized_y = (y.astype(np.float32) - height * 0.5) / height
world_x = normalized_x * depth[y, x] / fx
world_y = normalized_y * depth[y, x] / fy
world_z = depth[y, x]
ones = np.ones(world_z.shape[0], dtype=np.float32)
return np.vstack((world_x, world_y, world_z, ones)).T
def render(self, object_poses, render_pc=True):
assert(isinstance(object_poses, list))
assert(len(object_poses) == len(self._object_nodes))
all_transferred_poses = []
for object_pose, object_node, object_distance in zip(object_poses, self._object_nodes, self._object_distances):
transferred_pose = object_pose.copy()
transferred_pose[2, 3] = object_distance
all_transferred_poses.append(transferred_pose)
self._scene.set_pose(object_node, transferred_pose)
color, depth = self.renderer.render(self._scene)
if render_pc:
pc = self._to_pointcloud(depth)
else:
pc = None
return color, depth, pc, all_transferred_poses
def render_all_and_save_to_h5(self, output_path, all_eulers, vis=False):
"""
Args:
output_path: path of the h5 file.
all_eulers: list of 3 elemenet-tuples indicating the euler angles
in degrees.
"""
if len(self._object_nodes) != 1:
raise ValueError(
'object nodes should have 1 element, not {}'.format(len(self._object_nodes))
)
hf = h5py.File(output_path)
#point_grp = hf.create_group('points')
#pose_grp = hf.create_group('object_poses')
mean_grp = hf.create_dataset('object_mean', data=self._object_means[0])
pcs = []
rotations = []
#import mayavi.mlab as mlab
for i, euler in enumerate(all_eulers):
assert isinstance(euler, tuple) and len(euler) == 3
rotation = tra.euler_matrix(*euler)
color, _, pc, final_rotation = self.render([rotation])
MAX_POINTS = 3000
if pc.shape[0] > MAX_POINTS:
pc = pc[np.random.choice(range(pc.shape[0]), replace=False, size=MAX_POINTS), :]
elif pc.shape[0] < MAX_POINTS:
pc = pc[np.random.choice(range(pc.shape[0]), replace=True, size=MAX_POINTS), :]
#print('{}/{}: {}'.format(i, len(all_eulers), pc.shape))
cv2.imshow('w', color)
cv2.waitKey(1)
#mlab.figure()
#mlab.points3d(pc[:, 0], pc[:, 1], pc[:, 2])
#mlab.show()
key = '{}_{}_{}'.format(euler[0], euler[1], euler[2])
pcs.append(pc)
rotations.append(final_rotation[0])
hf.create_dataset('pcs', data=pcs, compression='gzip')
hf.create_dataset('object_poses', data=rotations, compression='gzip')
hf.close()
@property
def object_distances(self):
return self._object_distances
def main_check_pointcloud():
from train_vae_clean import draw_scene, inverse_transform
import mayavi.mlab as mlab
import matplotlib.pyplot as plt
renderer = ObjectRenderer(object_paths=['panda_gripper.obj'], object_scales=[1])
pcs = []
for _ in range(10):
object_pose = tra.euler_matrix(
np.random.rand() * np.pi * 2,
np.random.rand() * np.pi * 2,
np.random.rand() * np.pi * 2,
)
#object_pose = np.eye(4)
#object_pose[2, 3] = 0.8
color, depth, pc, object_pose = renderer.render([object_pose])
object_pose = object_pose[0]
plt.imshow(color)
draw_scene (
np.matmul(pc, inverse_transform(object_pose).T),
None,
mesh=renderer.tmesh
)
mlab.figure()
print(np.mean(pc, 0))
mlab.points3d(pc[:, 0], pc[:, 1], pc[:, 2], pc[:, 2], colormap='plasma')
#pcs.append(np.matmul(pc, inverse_transform(object_pose).T))
#print(pcs[-1].shape)
#draw_scene(pc, None)
plt.show()
mlab.show()
pc = np.concatenate(pcs, 0)
draw_scene(pc, None)
mlab.show()
def inverse_transform(trans):
rot = trans[:3, :3]
t = trans[:3, 3]
rot = np.transpose(rot)
t = -np.matmul(rot, t)
output = np.zeros((4, 4), dtype=np.float32)
output[3][3] = 1
output[:3, :3] = rot
output[:3, 3] = t
return output
def main(argv):
import argparse
parser = argparse.ArgumentParser(description='Pre-render objects',
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument('--cad_path', type=str, default=1)
parser.add_argument('--cad_scale', type=float, default=-1)
parser.add_argument('--quaternion_file', type=str, default='uniform_quaternions/data2_4608.qua')
parser.add_argument('--output_path', type=str)
args = parser.parse_args(sys.argv[1:])
if args.cad_scale <= 0:
raise ValueError("you have to set --cad_scale to positive number")
quaternions = [l[:-1].split('\t') for l in open(args.quaternion_file, 'r').readlines()]
quaternions = [[float(t[0]),
float(t[1]),
float(t[2]),
float(t[3])] for t in quaternions]
quaternions = np.asarray(quaternions)
quaternions = np.roll(quaternions, 1, axis=1)
all_eulers = [tra.euler_from_matrix(tra.quaternion_matrix(q)) for q in quaternions]
renderer = ObjectRenderer(object_paths=[args.cad_path], object_scales=[args.cad_scale])
try:
renderer.render_all_and_save_to_h5(args.output_path, all_eulers, vis=True)
except Exception as e:
print(e)
os.system('rm {}'.format(args.output_path))
if __name__ == '__main__':
main(sys.argv[1:])
#main_check_pointcloud()
#main_render_all((50, 50, 10), '/home/arsalan/data/models_selected/03797390/1bc5d303ff4d6e7e1113901b72a68e7c/model.stl', 0.17)