Python pybullet.computeViewMatrix() Examples
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code examples of pybullet.computeViewMatrix().
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Example #1
Source File: simulate.py From obman_train with GNU General Public License v3.0 | 6 votes |
def take_picture(renderer, width=256, height=256, scale=0.001, conn_id=None): view_matrix = p.computeViewMatrix( [0, 0, -1], [0, 0, 0], [0, -1, 0], physicsClientId=conn_id ) proj_matrix = p.computeProjectionMatrixFOV( 20, 1, 0.05, 2, physicsClientId=conn_id ) w, h, rgba, depth, mask = p.getCameraImage( width=width, height=height, projectionMatrix=proj_matrix, viewMatrix=view_matrix, renderer=renderer, physicsClientId=conn_id, ) return rgba
Example #2
Source File: renderer.py From mvp_grasp with BSD 3-Clause "New" or "Revised" License | 6 votes |
def render(self): if np.all(self._rendered_pos == self.camera_pos) and np.all(self._rendered_rot == self.camera_rot): return self._rendered target = self.camera_pos + np.dot(self.camera_rot, [0, 0, 1.0, 1.0])[0:3] up = np.dot(self.camera_rot, [0, -1.0, 0, 1.0])[0:3] vm = pb.computeViewMatrix(self.camera_pos, target, up) i_arr = pb.getCameraImage(self.im_width, self.im_height, vm, self.pm, shadow=0, renderer=pb.ER_TINY_RENDERER) # renderer=pb.ER_BULLET_HARDWARE_OPENGL) # Record the position of the camera, and don't re-render if it hasn't moved. self._rendered = i_arr self._rendered_pos = self.camera_pos.copy() self._rendered_rot = self.camera_rot.copy() return i_arr
Example #3
Source File: bullet_robot_env.py From Rainbow_ddpg with MIT License | 5 votes |
def __init__(self, n_actions, # Dimension of action vector. n_substeps, # Number of simulation steps to do in every env step. observation_type="low_dim", done_after=float("inf"), use_gui=False, frame_memory_len=0): self.n_substeps = n_substeps self.metadata = { 'render.modes': ['rgbd_array'], 'video.frames_per_second': int(np.round(1.0 / self.dt)) } self.numSteps = 0 if use_gui: physics_client = p.connect(p.GUI) else: physics_client = p.connect(p.DIRECT) self.p = PhysClientWrapper(p, physics_client) self.p.setAdditionalSearchPath(pybullet_data.getDataPath()) self.doneAfter = done_after self.observation_type = observation_type self.seed() self.frameMemoryLen = frame_memory_len if frame_memory_len: self.frameMemory = deque(maxlen=frame_memory_len) self.viewMatrix = p.computeViewMatrix([-1.05, 0, 0.68], [0.1, 0, 0], [-0.5, 0, 1]) self.projMatrix = p.computeProjectionMatrixFOV( fov=45, aspect=4. / 3., nearVal=0.01, farVal=2.5) self.light = { "diffuse": 0.4, "ambient": 0.5, "spec": 0.2, "dir": [10, 10, 100], "col": [1, 1, 1] } self._env_setup(initial_qpos=None) self.action_space = spaces.Box( -1, 1, shape=(n_actions, ), dtype='float32') self.pixels_space = spaces.Box( -np.inf, np.inf, shape=(84, 84, 3), dtype='float32') if observation_type == "low_dim": self.observation_space = self.low_dim_space elif observation_type == "pixels": self.observation_space = self.pixels_space elif observation_type == "pixels_stacked": self.observation_space = spaces.Box( -np.inf, np.inf, shape=(84, 84, 12), dtype='float32') elif observation_type == "pixels_depth": self.observation_space = spaces.Box( -np.inf, np.inf, shape=(84, 84), dtype='float32') else: raise Exception("Unimplemented observation_type")
Example #4
Source File: camera.py From qibullet with Apache License 2.0 | 5 votes |
def _getCameraImage(self): """ INTERNAL METHOD, Computes the OpenGL virtual camera image. The resolution and the projection matrix have to be computed before calling this method, or it will crash Returns: camera_image - The camera image of the OpenGL virtual camera """ _, _, _, _, pos_world, q_world = pybullet.getLinkState( self.robot_model, self.camera_link.getParentIndex(), computeForwardKinematics=False, physicsClientId=self.physics_client) rotation = pybullet.getMatrixFromQuaternion(q_world) forward_vector = [rotation[0], rotation[3], rotation[6]] up_vector = [rotation[2], rotation[5], rotation[8]] camera_target = [ pos_world[0] + forward_vector[0] * 10, pos_world[1] + forward_vector[1] * 10, pos_world[2] + forward_vector[2] * 10] view_matrix = pybullet.computeViewMatrix( pos_world, camera_target, up_vector, physicsClientId=self.physics_client) with self.resolution_lock: camera_image = pybullet.getCameraImage( self.resolution.width, self.resolution.height, view_matrix, self.projection_matrix, renderer=pybullet.ER_BULLET_HARDWARE_OPENGL, flags=pybullet.ER_NO_SEGMENTATION_MASK, physicsClientId=self.physics_client) return camera_image
Example #5
Source File: helloworld_panda.py From pybullet-robot-envs with GNU Lesser General Public License v2.1 | 5 votes |
def render(robot): pos, rot, _, _, _, _ = p.getLinkState(robot.robot_id, linkIndex=robot.end_eff_idx, computeForwardKinematics=True) rot_matrix = p.getMatrixFromQuaternion(rot) rot_matrix = np.array(rot_matrix).reshape(3, 3) # camera params height = 640 width = 480 fx, fy = 596.6278076171875, 596.6278076171875 cx, cy = 311.98663330078125, 236.76170349121094 near, far = 0.1, 10 camera_vector = rot_matrix.dot((0, 0, 1)) up_vector = rot_matrix.dot((0, -1, 0)) camera_eye_pos = np.array(pos) camera_target_position = camera_eye_pos + 0.2 * camera_vector view_matrix = p.computeViewMatrix(camera_eye_pos, camera_target_position, up_vector) proj_matrix = (2.0 * fx / width, 0.0, 0.0, 0.0, 0.0, 2.0 * fy / height, 0.0, 0.0, 1.0 - 2.0 * cx / width, 2.0 * cy / height - 1.0, (far + near) / (near - far), -1.0, 0.0, 0.0, 2.0 * far * near / (near - far), 0.0) p.getCameraImage(width=width, height=height, viewMatrix=view_matrix, projectionMatrix=proj_matrix, renderer=p.ER_BULLET_HARDWARE_OPENGL) # renderer=self._p.ER_TINY_RENDERER)
Example #6
Source File: bullet_world.py From NTP-vat-release with MIT License | 4 votes |
def __init__(self, display=True, data_dir='./data', verbose=False, key=None, camera_params={}): self._pe = BulletPhysicsEngine() self._display = display self._data_dir = data_dir self._verbose = verbose self._bodies = None self._robots = None self._time_step = None self._ctrl_listeners = [] self._key_dict = None self._key_act_dict = None self._modifier_dict = None # Camera Parameters fov = camera_params.get('fov', 60) aspect = camera_params.get('aspect', 1) near = camera_params.get('near', 0.02) far = camera_params.get('far', 1) view_matrix = camera_params.get( 'view_matrix', [[0.0, -0.4, 1.4], [0, 0.0, 0], [1, 0, 0]] ) self.view_matrix = p.computeViewMatrix(*view_matrix) self.projection_matrix = p.computeProjectionMatrixFOV( fov, aspect, near, far) self.video_log_key = 0 # Connect to the simulation # TODO(Kuan): If VR # p.connect(p.SHARED_MEMORY) if self._display: p.connect(p.GUI) else: if key is None: p.connect(p.DIRECT) else: p.connect(p.DIRECT, key=key)
Example #7
Source File: turtlebot_pybullet.py From SocialRobot with Apache License 2.0 | 4 votes |
def get_image(cam_pos, cam_orientation): """ Arguments cam_pos: camera position cam_orientation: camera orientation in quaternion """ width = 160 height = 120 fov = 90 aspect = width / height near = 0.001 far = 5 if use_maximal_coordinates: # cam_orientation has problem when enable bt_rigid_body, # looking at 0.0, 0.0, 0.0 instead # this does not affect performance cam_pos_offset = cam_pos + np.array([0.0, 0.0, 0.3]) target_pos = np.array([0.0, 0.0, 0.0]) else: # camera pos, look at, camera up direction rot_matrix = p.getMatrixFromQuaternion(cam_orientation) # offset to base pos cam_pos_offset = cam_pos + np.dot( np.array(rot_matrix).reshape(3, 3), np.array([0.1, 0.0, 0.3])) target_pos = cam_pos_offset + np.dot( np.array(rot_matrix).reshape(3, 3), np.array([-1.0, 0.0, 0.0])) # compute view matrix view_matrix = p.computeViewMatrix(cam_pos_offset, target_pos, [0, 0, 1]) projection_matrix = p.computeProjectionMatrixFOV(fov, aspect, near, far) # Get depth values using the OpenGL renderer if enable_open_gl_rendering: w, h, rgb, depth, seg = p.getCameraImage( width, height, view_matrix, projection_matrix, shadow=True, renderer=p.ER_BULLET_HARDWARE_OPENGL) else: w, h, rgb, depth, seg = p.getCameraImage( width, height, view_matrix, projection_matrix, shadow=True, renderer=p.ER_TINY_RENDERER) # depth_buffer = np.reshape(images[3], [width, height]) # depth = far * near / (far - (far - near) * depth_buffer) # seg = np.reshape(images[4],[width,height])*1./255. return rgb