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NVIDIA CORPORATION and its licensors retain all intellectual property
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Isaac Gym Graphics Example
--------------------------
This example demonstrates the ability to change the up axis used in Isaac Gym.
The default option is to set Y as up axis. Using gymapi.UpAxis.UP_AXIS_Z, we can
change orientation such that Z is up for both the Viewer and camera sensors.
Requires Pillow (formerly PIL) to write images from python. Use `pip install pillow`
to get Pillow.
"""
import os
import numpy as np
from isaacgym import gymapi
from isaacgym import gymutil
# acquire the gym interface
gym = gymapi.acquire_gym()
# parse arguments
args = gymutil.parse_arguments(description="Graphics Example",
headless=True,
custom_parameters=[
{"name": "--save_images", "action": "store_true", "help": "Write RGB and Depth Images To Disk"},
{"name": "--up_axis_z", "action": "store_true", "help": ""}])
if args.save_images:
from PIL import Image as im
# get default params
sim_params = gymapi.SimParams()
if args.up_axis_z:
sim_params.up_axis = gymapi.UpAxis.UP_AXIS_Z
sim_params.gravity = gymapi.Vec3(0.0, 0.0, -9.8)
sim_params.flex.shape_collision_margin = 0.04
sim_params.use_gpu_pipeline = False
if args.use_gpu_pipeline:
print("WARNING: Forcing CPU pipeline.")
# create sim
sim = gym.create_sim(args.compute_device_id, args.graphics_device_id, args.physics_engine, sim_params)
if sim is None:
print("*** Failed to create sim")
quit()
# Create a default ground plane
plane_params = gymapi.PlaneParams()
if args.up_axis_z:
plane_params.normal = gymapi.Vec3(0.0, 0.0, 1.0)
plane_params.distance = 2.0
gym.add_ground(sim, plane_params)
if not args.headless:
# create viewer using the default camera properties
viewer = gym.create_viewer(sim, gymapi.CameraProperties())
if viewer is None:
raise ValueError('*** Failed to create viewer')
# set up the env grid
num_envs = 1
spacing = 2.0
env_lower = gymapi.Vec3(-spacing, 0.0, -spacing)
env_upper = gymapi.Vec3(spacing, spacing, spacing)
# list of assets which are used in this example
repeat_assets = 8
asset_files = []
asset_root = "../../assets"
for i in range(repeat_assets):
asset_files.append("urdf/ball.urdf")
# Load all assets
assets = []
for i in range(len(asset_files)):
asset_handle = gym.load_asset(sim, asset_root, asset_files[i])
assets.append(asset_handle)
# Create environments
actor_handles = [[]]
envs = []
# create environments
for i in range(num_envs):
actor_handles.append([])
env = gym.create_env(sim, env_lower, env_upper, 4)
envs.append(env)
num_assets = len(assets)
for j in range(num_assets):
# Lay out assets in a grid within the environment. Start actor 0 at a height of 10 so
# the camera attachment is apparent in output images
grid = np.ceil(np.sqrt(num_assets))
d = 2 * spacing / grid
x = d * (0.5 + np.mod(j, grid))
y = 6.0
z = d * (0.5 + np.floor(j/grid))
actor_pose = gymapi.Transform()
if sim_params.up_axis == gymapi.UpAxis.UP_AXIS_Z:
actor_pose.p = gymapi.Vec3(x, z, y)
else:
actor_pose.p = gymapi.Vec3(x, y, z)
actor_pose.r = gymapi.Quat(-0.707107, 0.0, 0.0, 0.707107)
asset_name = "asset_%d" % j
handle = gym.create_actor(env, assets[j], actor_pose, asset_name, i, 1, 0)
actor_handles[i].append(handle)
# Create 2 cameras in each environment, one which views the origin of the environment
# and one which is attached to the 0th body of the 0th actor and moves with that actor
if sim_params.up_axis == gymapi.UpAxis.UP_AXIS_Z:
camera_position = gymapi.Vec3(4.0, 14.0, 10.0)
else:
camera_position = gymapi.Vec3(14.0, 10.0, 4.0)
camera_target = gymapi.Vec3(0, 0, 0)
gym.viewer_camera_look_at(viewer, None, camera_position, camera_target)
camera_handles = [[]]
for i in range(num_envs):
camera_handles.append([])
camera_properties = gymapi.CameraProperties()
camera_properties.width = 360
camera_properties.height = 240
# Set a fixed position and look-target for the first camera
# position and target location are in the coordinate frame of the environment
h1 = gym.create_camera_sensor(envs[i], camera_properties)
gym.set_camera_location(h1, envs[i], camera_position, camera_target)
camera_handles[i].append(h1)
if not os.path.exists("graphics_images"):
os.mkdir("graphics_images")
frame_count = 0
# Main simulation loop
while True:
# step the physics simulation
gym.simulate(sim)
gym.fetch_results(sim, True)
# communicate physics to graphics system
gym.step_graphics(sim)
# render the camera sensors
gym.render_all_camera_sensors(sim)
if args.save_images and np.mod(frame_count, 30) == 0:
for i in range(num_envs):
for j in range(1):
# The gym utility to write images to disk is recommended only for RGB images.
rgb_filename = "graphics_images/rgb_env%d_cam%d_frame%d.png" % (i, j, frame_count)
gym.write_camera_image_to_file(sim, envs[i], camera_handles[i][j], gymapi.IMAGE_COLOR, rgb_filename)
if not args.headless:
# render the viewer
gym.draw_viewer(viewer, sim, True)
# Wait for dt to elapse in real time to sync viewer with
# simulation rate. Not necessary in headless.
gym.sync_frame_time(sim)
# Check for exit condition - user closed the viewer window
if gym.query_viewer_has_closed(viewer):
break
frame_count = frame_count + 1
print('Done')
# cleanup
gym.destroy_viewer(viewer)
gym.destroy_sim(sim)
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