robosuite.renderers.nvisii package
Contents
robosuite.renderers.nvisii package#
Submodules#
robosuite.renderers.nvisii.nvisii_renderer module#
- class robosuite.renderers.nvisii.nvisii_renderer.NVISIIRenderer(env, img_path='images/', width=500, height=500, spp=256, use_noise=False, debug_mode=False, video_mode=False, video_path='videos/', video_name='robosuite_video_0.mp4', video_fps=60, verbose=1, vision_modalities=None)#
Bases:
robosuite.renderers.base.Renderer
- close()#
Deinitializes the nvisii rendering environment
- get_pixel_obs()#
Get the pixel observations from the given renderer
- Returns
numpy array representing pixels of renderer
- Return type
numpyarr
- randomize_colors(N, bright=True)#
Modified from https://github.com/matterport/Mask_RCNN/blob/master/mrcnn/visualize.py#L59 Generate random colors. To get visually distinct colors, generate them in HSV space then convert to RGB.
- render(render_type='png')#
Renders an image of the NVISII renderer
- Parameters
render_type (string, optional) – Type of file to save as. Defaults to ‘png’
- render_data_to_file(img_file)#
- render_segmentation_data(img_file)#
- render_to_file(img_file)#
- reset()#
Reset the renderer with initial states for environment
- segmentation_to_rgb(seg_im, random_colors=False)#
Helper function to visualize segmentations as RGB frames. NOTE: assumes that geom IDs go up to 255 at most - if not, multiple geoms might be assigned to the same color.
- set_camera_pos_quat(pos, quat)#
- tag_in_name(name)#
Checks if one of the tags in body tags in the name
- Parameters
name (string) – Name of component
- update()#
Updates the states for the wrapper given a certain action
- Parameters
action (np-array) – The action the robot should take
robosuite.renderers.nvisii.nvisii_utils module#
- robosuite.renderers.nvisii.nvisii_utils.load_object(geom, geom_name, geom_type, geom_quat, geom_pos, geom_size, geom_scale, geom_rgba, geom_tex_name, geom_tex_file, class_id, meshes)#
Function that initializes the meshes in the memory.
- Parameters
geom (XML element) – Object in XML file to load
geom_name (str) – Name for the object.
geom_type (str) – Type of the object. Types include “box”, “cylinder”, or “mesh”.
geom_quat (array) – Quaternion (wxyz) of the object.
geom_pos (array) – Position of the object.
geom_size (array) – Size of the object.
geom_scale (array) – Scale of the object.
geom_rgba (array) – Color of the object. This is only used if the geom type is not a mesh and there is no specified material.
geom_tex_name (str) – Name of the texture for the object
geom_tex_file (str) – File of the texture for the object
class_id (int) – Class id for the component
meshes (dict) – Meshes for the object
robosuite.renderers.nvisii.parser module#
- class robosuite.renderers.nvisii.parser.Components(obj, geom_index, element_id, parent_body_name, geom_pos, geom_quat, dynamic)#
Bases:
tuple
- dynamic#
Alias for field number 6
- element_id#
Alias for field number 2
- geom_index#
Alias for field number 1
- geom_pos#
Alias for field number 4
- geom_quat#
Alias for field number 5
- obj#
Alias for field number 0
- parent_body_name#
Alias for field number 3
- class robosuite.renderers.nvisii.parser.Parser(renderer, env, segmentation_type)#
Bases:
robosuite.renderers.base_parser.BaseParser
- create_class_mapping()#
Create class name to index mapping for both semantic and instance segmentation.
- get_class_id(geom_index, element_id)#
Given index of the geom object get the class id based on self.segmentation type.
- parse_geometries()#
Iterate through each goemetry and load it in the NVISII renderer.
- parse_materials()#
Parse all materials and use texture mapping to initialize materials
- parse_meshes()#
Create mapping of meshes.
- parse_textures()#
Parse and load all textures and store them
- tag_in_name(name, tags)#
Checks if one of the tags in body tags in the name
- Parameters
name (str) – Name of geom element.
tags (array) – List of keywords to check from.