Add pusht as package

This commit is contained in:
Simon Alibert 2024-03-29 12:03:49 +01:00
parent 1d7ff65dc5
commit c6002bb88f
10 changed files with 82 additions and 674 deletions

24
.github/poetry/cpu/poetry.lock generated vendored
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@ -2892,6 +2892,25 @@ numpy = ">=1.14,<2"
docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
test = ["pytest", "pytest-cov"]
[[package]]
name = "sim-pusht"
version = "0.1.0"
description = "PushT environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_pusht-0.1.0-py3-none-any.whl", hash = "sha256:1348dcab5ea8460eff2dc97b7d62dd40f2a382df92bfdc69ff5c0224900690b0"},
{file = "sim_pusht-0.1.0.tar.gz", hash = "sha256:d8f6a2207fd781348156206728329aa6338e9785cfc07679c5c48889b34d9b14"},
]
[package.dependencies]
gymnasium = ">=0.29.1,<0.30.0"
opencv-python = ">=4.9.0.80,<5.0.0.0"
pygame = ">=2.5.2,<3.0.0"
pymunk = ">=6.6.0,<7.0.0"
scikit-image = ">=0.22.0,<0.23.0"
shapely = ">=2.0.3,<3.0.0"
[[package]]
name = "six"
version = "1.16.0"
@ -3327,7 +3346,10 @@ files = [
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
[extras]
pusht = ["sim-pusht"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "8800bb8b24312d17b765cd2ce2799f49436171dd5fbf1bec3b07f853cfa9befd"
content-hash = "1111059e284866eabaf47b85fbb7b3785b10317feb6439f7616da3a485a17520"

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@ -1,19 +1,23 @@
[tool.poetry]
name = "lerobot"
version = "0.1.0"
description = "Le robot is learning"
description = "🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch"
authors = [
"Rémi Cadène <re.cadene@gmail.com>",
]
maintainers = [
"Alexander Soare <alexander.soare159@gmail.com>",
"Simon Alibert <alibert.sim@gmail.com>",
]
repository = "https://github.com/Cadene/lerobot"
readme = "README.md"
license = "MIT"
license = "Apache-2.0"
keywords = ["robotics, deep, reinforcement, learning, pytorch"]
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: MIT License",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
]
packages = [{include = "lerobot"}]
@ -53,11 +57,19 @@ huggingface-hub = "^0.21.4"
gymnasium-robotics = "^1.2.4"
gymnasium = "^0.29.1"
cmake = "^3.29.0.1"
sim-pusht = { version = "^0.1.0", optional = true}
[tool.poetry.extras]
pusht = ["sim-pusht"]
[tool.poetry.group.dev.dependencies]
pre-commit = "^3.6.2"
debugpy = "^1.8.1"
[tool.poetry.group.test.dependencies]
pytest = "^8.1.0"
pytest-cov = "^5.0.0"

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@ -87,7 +87,7 @@ jobs:
TMP: ~/tmp
run: |
mkdir ~/tmp
poetry install --no-interaction --no-root
poetry install --no-interaction --no-root --without dev --extras pusht
- name: Save cached venv
if: |

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@ -15,8 +15,8 @@ from torchrl.data.replay_buffers.writers import Writer
from lerobot.common.datasets.abstract import AbstractDataset
from lerobot.common.datasets.utils import download_and_extract_zip
from lerobot.common.envs.pusht.pusht_env import pymunk_to_shapely
from lerobot.common.policies.diffusion.replay_buffer import ReplayBuffer as DiffusionPolicyReplayBuffer
from pusht.pusht_env import pymunk_to_shapely
# as define in env
SUCCESS_THRESHOLD = 0.95 # 95% coverage,

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@ -59,7 +59,7 @@ class PushtEnv(AbstractEnv):
if not self.from_pixels:
raise NotImplementedError("Use PushTEnv, instead of PushTImageEnv")
from lerobot.common.envs.pusht.pusht_image_env import PushTImageEnv
from pusht.pusht_image_env import PushTImageEnv
self._env = PushTImageEnv(render_size=self.image_size)

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@ -1,378 +0,0 @@
import collections
import cv2
import gymnasium as gym
import numpy as np
import pygame
import pymunk
import pymunk.pygame_util
import shapely.geometry as sg
import skimage.transform as st
from gymnasium import spaces
from pymunk.vec2d import Vec2d
from lerobot.common.envs.pusht.pymunk_override import DrawOptions
def pymunk_to_shapely(body, shapes):
geoms = []
for shape in shapes:
if isinstance(shape, pymunk.shapes.Poly):
verts = [body.local_to_world(v) for v in shape.get_vertices()]
verts += [verts[0]]
geoms.append(sg.Polygon(verts))
else:
raise RuntimeError(f"Unsupported shape type {type(shape)}")
geom = sg.MultiPolygon(geoms)
return geom
class PushTEnv(gym.Env):
metadata = {"render.modes": ["human", "rgb_array"], "video.frames_per_second": 10}
reward_range = (0.0, 1.0)
def __init__(
self,
legacy=True, # compatibility with original
block_cog=None,
damping=None,
render_action=True,
render_size=96,
reset_to_state=None,
):
self._seed = None
self.seed()
self.window_size = ws = 512 # The size of the PyGame window
self.render_size = render_size
self.sim_hz = 100
# Local controller params.
self.k_p, self.k_v = 100, 20 # PD control.z
self.control_hz = self.metadata["video.frames_per_second"]
# legcay set_state for data compatibility
self.legacy = legacy
# agent_pos, block_pos, block_angle
self.observation_space = spaces.Box(
low=np.array([0, 0, 0, 0, 0], dtype=np.float64),
high=np.array([ws, ws, ws, ws, np.pi * 2], dtype=np.float64),
shape=(5,),
dtype=np.float64,
)
# positional goal for agent
self.action_space = spaces.Box(
low=np.array([0, 0], dtype=np.float64),
high=np.array([ws, ws], dtype=np.float64),
shape=(2,),
dtype=np.float64,
)
self.block_cog = block_cog
self.damping = damping
self.render_action = render_action
"""
If human-rendering is used, `self.window` will be a reference
to the window that we draw to. `self.clock` will be a clock that is used
to ensure that the environment is rendered at the correct framerate in
human-mode. They will remain `None` until human-mode is used for the
first time.
"""
self.window = None
self.clock = None
self.screen = None
self.space = None
self.teleop = None
self.render_buffer = None
self.latest_action = None
self.reset_to_state = reset_to_state
def reset(self):
seed = self._seed
self._setup()
if self.block_cog is not None:
self.block.center_of_gravity = self.block_cog
if self.damping is not None:
self.space.damping = self.damping
# use legacy RandomState for compatibility
state = self.reset_to_state
if state is None:
rs = np.random.RandomState(seed=seed)
state = np.array(
[
rs.randint(50, 450),
rs.randint(50, 450),
rs.randint(100, 400),
rs.randint(100, 400),
rs.randn() * 2 * np.pi - np.pi,
]
)
self._set_state(state)
observation = self._get_obs()
return observation
def step(self, action):
dt = 1.0 / self.sim_hz
self.n_contact_points = 0
n_steps = self.sim_hz // self.control_hz
if action is not None:
self.latest_action = action
for _ in range(n_steps):
# Step PD control.
# self.agent.velocity = self.k_p * (act - self.agent.position) # P control works too.
acceleration = self.k_p * (action - self.agent.position) + self.k_v * (
Vec2d(0, 0) - self.agent.velocity
)
self.agent.velocity += acceleration * dt
# Step physics.
self.space.step(dt)
# compute reward
goal_body = self._get_goal_pose_body(self.goal_pose)
goal_geom = pymunk_to_shapely(goal_body, self.block.shapes)
block_geom = pymunk_to_shapely(self.block, self.block.shapes)
intersection_area = goal_geom.intersection(block_geom).area
goal_area = goal_geom.area
coverage = intersection_area / goal_area
reward = np.clip(coverage / self.success_threshold, 0, 1)
done = coverage > self.success_threshold
observation = self._get_obs()
info = self._get_info()
return observation, reward, done, info
def render(self, mode):
return self._render_frame(mode)
def teleop_agent(self):
TeleopAgent = collections.namedtuple("TeleopAgent", ["act"])
def act(obs):
act = None
mouse_position = pymunk.pygame_util.from_pygame(Vec2d(*pygame.mouse.get_pos()), self.screen)
if self.teleop or (mouse_position - self.agent.position).length < 30:
self.teleop = True
act = mouse_position
return act
return TeleopAgent(act)
def _get_obs(self):
obs = np.array(
tuple(self.agent.position) + tuple(self.block.position) + (self.block.angle % (2 * np.pi),)
)
return obs
def _get_goal_pose_body(self, pose):
mass = 1
inertia = pymunk.moment_for_box(mass, (50, 100))
body = pymunk.Body(mass, inertia)
# preserving the legacy assignment order for compatibility
# the order here doesn't matter somehow, maybe because CoM is aligned with body origin
body.position = pose[:2].tolist()
body.angle = pose[2]
return body
def _get_info(self):
n_steps = self.sim_hz // self.control_hz
n_contact_points_per_step = int(np.ceil(self.n_contact_points / n_steps))
info = {
"pos_agent": np.array(self.agent.position),
"vel_agent": np.array(self.agent.velocity),
"block_pose": np.array(list(self.block.position) + [self.block.angle]),
"goal_pose": self.goal_pose,
"n_contacts": n_contact_points_per_step,
}
return info
def _render_frame(self, mode):
if self.window is None and mode == "human":
pygame.init()
pygame.display.init()
self.window = pygame.display.set_mode((self.window_size, self.window_size))
if self.clock is None and mode == "human":
self.clock = pygame.time.Clock()
canvas = pygame.Surface((self.window_size, self.window_size))
canvas.fill((255, 255, 255))
self.screen = canvas
draw_options = DrawOptions(canvas)
# Draw goal pose.
goal_body = self._get_goal_pose_body(self.goal_pose)
for shape in self.block.shapes:
goal_points = [
pymunk.pygame_util.to_pygame(goal_body.local_to_world(v), draw_options.surface)
for v in shape.get_vertices()
]
goal_points += [goal_points[0]]
pygame.draw.polygon(canvas, self.goal_color, goal_points)
# Draw agent and block.
self.space.debug_draw(draw_options)
if mode == "human":
# The following line copies our drawings from `canvas` to the visible window
self.window.blit(canvas, canvas.get_rect())
pygame.event.pump()
pygame.display.update()
# the clock is already ticked during in step for "human"
img = np.transpose(np.array(pygame.surfarray.pixels3d(canvas)), axes=(1, 0, 2))
img = cv2.resize(img, (self.render_size, self.render_size))
if self.render_action and self.latest_action is not None:
action = np.array(self.latest_action)
coord = (action / 512 * 96).astype(np.int32)
marker_size = int(8 / 96 * self.render_size)
thickness = int(1 / 96 * self.render_size)
cv2.drawMarker(
img,
coord,
color=(255, 0, 0),
markerType=cv2.MARKER_CROSS,
markerSize=marker_size,
thickness=thickness,
)
return img
def close(self):
if self.window is not None:
pygame.display.quit()
pygame.quit()
def seed(self, seed=None):
if seed is None:
seed = np.random.randint(0, 25536)
self._seed = seed
self.np_random = np.random.default_rng(seed)
def _handle_collision(self, arbiter, space, data):
self.n_contact_points += len(arbiter.contact_point_set.points)
def _set_state(self, state):
if isinstance(state, np.ndarray):
state = state.tolist()
pos_agent = state[:2]
pos_block = state[2:4]
rot_block = state[4]
self.agent.position = pos_agent
# setting angle rotates with respect to center of mass
# therefore will modify the geometric position
# if not the same as CoM
# therefore should be modified first.
if self.legacy:
# for compatibility with legacy data
self.block.position = pos_block
self.block.angle = rot_block
else:
self.block.angle = rot_block
self.block.position = pos_block
# Run physics to take effect
self.space.step(1.0 / self.sim_hz)
def _set_state_local(self, state_local):
agent_pos_local = state_local[:2]
block_pose_local = state_local[2:]
tf_img_obj = st.AffineTransform(translation=self.goal_pose[:2], rotation=self.goal_pose[2])
tf_obj_new = st.AffineTransform(translation=block_pose_local[:2], rotation=block_pose_local[2])
tf_img_new = st.AffineTransform(matrix=tf_img_obj.params @ tf_obj_new.params)
agent_pos_new = tf_img_new(agent_pos_local)
new_state = np.array(list(agent_pos_new[0]) + list(tf_img_new.translation) + [tf_img_new.rotation])
self._set_state(new_state)
return new_state
def _setup(self):
self.space = pymunk.Space()
self.space.gravity = 0, 0
self.space.damping = 0
self.teleop = False
self.render_buffer = []
# Add walls.
walls = [
self._add_segment((5, 506), (5, 5), 2),
self._add_segment((5, 5), (506, 5), 2),
self._add_segment((506, 5), (506, 506), 2),
self._add_segment((5, 506), (506, 506), 2),
]
self.space.add(*walls)
# Add agent, block, and goal zone.
self.agent = self.add_circle((256, 400), 15)
self.block = self.add_tee((256, 300), 0)
self.goal_color = pygame.Color("LightGreen")
self.goal_pose = np.array([256, 256, np.pi / 4]) # x, y, theta (in radians)
# Add collision handling
self.collision_handeler = self.space.add_collision_handler(0, 0)
self.collision_handeler.post_solve = self._handle_collision
self.n_contact_points = 0
self.max_score = 50 * 100
self.success_threshold = 0.95 # 95% coverage.
def _add_segment(self, a, b, radius):
shape = pymunk.Segment(self.space.static_body, a, b, radius)
shape.color = pygame.Color("LightGray") # https://htmlcolorcodes.com/color-names
return shape
def add_circle(self, position, radius):
body = pymunk.Body(body_type=pymunk.Body.KINEMATIC)
body.position = position
body.friction = 1
shape = pymunk.Circle(body, radius)
shape.color = pygame.Color("RoyalBlue")
self.space.add(body, shape)
return body
def add_box(self, position, height, width):
mass = 1
inertia = pymunk.moment_for_box(mass, (height, width))
body = pymunk.Body(mass, inertia)
body.position = position
shape = pymunk.Poly.create_box(body, (height, width))
shape.color = pygame.Color("LightSlateGray")
self.space.add(body, shape)
return body
def add_tee(self, position, angle, scale=30, color="LightSlateGray", mask=None):
if mask is None:
mask = pymunk.ShapeFilter.ALL_MASKS()
mass = 1
length = 4
vertices1 = [
(-length * scale / 2, scale),
(length * scale / 2, scale),
(length * scale / 2, 0),
(-length * scale / 2, 0),
]
inertia1 = pymunk.moment_for_poly(mass, vertices=vertices1)
vertices2 = [
(-scale / 2, scale),
(-scale / 2, length * scale),
(scale / 2, length * scale),
(scale / 2, scale),
]
inertia2 = pymunk.moment_for_poly(mass, vertices=vertices1)
body = pymunk.Body(mass, inertia1 + inertia2)
shape1 = pymunk.Poly(body, vertices1)
shape2 = pymunk.Poly(body, vertices2)
shape1.color = pygame.Color(color)
shape2.color = pygame.Color(color)
shape1.filter = pymunk.ShapeFilter(mask=mask)
shape2.filter = pymunk.ShapeFilter(mask=mask)
body.center_of_gravity = (shape1.center_of_gravity + shape2.center_of_gravity) / 2
body.position = position
body.angle = angle
body.friction = 1
self.space.add(body, shape1, shape2)
return body

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@ -1,41 +0,0 @@
import numpy as np
from gymnasium import spaces
from lerobot.common.envs.pusht.pusht_env import PushTEnv
class PushTImageEnv(PushTEnv):
metadata = {"render.modes": ["rgb_array"], "video.frames_per_second": 10}
# Note: legacy defaults to True for compatibility with original
def __init__(self, legacy=True, block_cog=None, damping=None, render_size=96):
super().__init__(
legacy=legacy, block_cog=block_cog, damping=damping, render_size=render_size, render_action=False
)
ws = self.window_size
self.observation_space = spaces.Dict(
{
"image": spaces.Box(low=0, high=1, shape=(3, render_size, render_size), dtype=np.float32),
"agent_pos": spaces.Box(low=0, high=ws, shape=(2,), dtype=np.float32),
}
)
self.render_cache = None
def _get_obs(self):
img = super()._render_frame(mode="rgb_array")
agent_pos = np.array(self.agent.position)
img_obs = np.moveaxis(img, -1, 0)
obs = {"image": img_obs, "agent_pos": agent_pos}
self.render_cache = img
return obs
def render(self, mode):
assert mode == "rgb_array"
if self.render_cache is None:
self._get_obs()
return self.render_cache

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@ -1,244 +0,0 @@
# ----------------------------------------------------------------------------
# pymunk
# Copyright (c) 2007-2016 Victor Blomqvist
#
# Permission is hereby granted, free of charge, to any person obtaining a copy
# of this software and associated documentation files (the "Software"), to deal
# in the Software without restriction, including without limitation the rights
# to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
# copies of the Software, and to permit persons to whom the Software is
# furnished to do so, subject to the following conditions:
#
# The above copyright notice and this permission notice shall be included in
# all copies or substantial portions of the Software.
#
# THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
# IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
# FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
# AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
# LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
# OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
# SOFTWARE.
# ----------------------------------------------------------------------------
"""This submodule contains helper functions to help with quick prototyping
using pymunk together with pygame.
Intended to help with debugging and prototyping, not for actual production use
in a full application. The methods contained in this module is opinionated
about your coordinate system and not in any way optimized.
"""
__docformat__ = "reStructuredText"
__all__ = [
"DrawOptions",
"get_mouse_pos",
"to_pygame",
"from_pygame",
# "lighten",
"positive_y_is_up",
]
from typing import Sequence, Tuple
import numpy as np
import pygame
import pymunk
from pymunk.space_debug_draw_options import SpaceDebugColor
from pymunk.vec2d import Vec2d
positive_y_is_up: bool = False
"""Make increasing values of y point upwards.
When True::
y
^
| . (3, 3)
|
| . (2, 2)
|
+------ > x
When False::
+------ > x
|
| . (2, 2)
|
| . (3, 3)
v
y
"""
class DrawOptions(pymunk.SpaceDebugDrawOptions):
def __init__(self, surface: pygame.Surface) -> None:
"""Draw a pymunk.Space on a pygame.Surface object.
Typical usage::
>>> import pymunk
>>> surface = pygame.Surface((10,10))
>>> space = pymunk.Space()
>>> options = pymunk.pygame_util.DrawOptions(surface)
>>> space.debug_draw(options)
You can control the color of a shape by setting shape.color to the color
you want it drawn in::
>>> c = pymunk.Circle(None, 10)
>>> c.color = pygame.Color("pink")
See pygame_util.demo.py for a full example
Since pygame uses a coordinate system where y points down (in contrast
to many other cases), you either have to make the physics simulation
with Pymunk also behave in that way, or flip everything when you draw.
The easiest is probably to just make the simulation behave the same
way as Pygame does. In that way all coordinates used are in the same
orientation and easy to reason about::
>>> space = pymunk.Space()
>>> space.gravity = (0, -1000)
>>> body = pymunk.Body()
>>> body.position = (0, 0) # will be positioned in the top left corner
>>> space.debug_draw(options)
To flip the drawing its possible to set the module property
:py:data:`positive_y_is_up` to True. Then the pygame drawing will flip
the simulation upside down before drawing::
>>> positive_y_is_up = True
>>> body = pymunk.Body()
>>> body.position = (0, 0)
>>> # Body will be position in bottom left corner
:Parameters:
surface : pygame.Surface
Surface that the objects will be drawn on
"""
self.surface = surface
super().__init__()
def draw_circle(
self,
pos: Vec2d,
angle: float,
radius: float,
outline_color: SpaceDebugColor,
fill_color: SpaceDebugColor,
) -> None:
p = to_pygame(pos, self.surface)
pygame.draw.circle(self.surface, fill_color.as_int(), p, round(radius), 0)
pygame.draw.circle(self.surface, light_color(fill_color).as_int(), p, round(radius - 4), 0)
# circle_edge = pos + Vec2d(radius, 0).rotated(angle)
# p2 = to_pygame(circle_edge, self.surface)
# line_r = 2 if radius > 20 else 1
# pygame.draw.lines(self.surface, outline_color.as_int(), False, [p, p2], line_r)
def draw_segment(self, a: Vec2d, b: Vec2d, color: SpaceDebugColor) -> None:
p1 = to_pygame(a, self.surface)
p2 = to_pygame(b, self.surface)
pygame.draw.aalines(self.surface, color.as_int(), False, [p1, p2])
def draw_fat_segment(
self,
a: Tuple[float, float],
b: Tuple[float, float],
radius: float,
outline_color: SpaceDebugColor,
fill_color: SpaceDebugColor,
) -> None:
p1 = to_pygame(a, self.surface)
p2 = to_pygame(b, self.surface)
r = round(max(1, radius * 2))
pygame.draw.lines(self.surface, fill_color.as_int(), False, [p1, p2], r)
if r > 2:
orthog = [abs(p2[1] - p1[1]), abs(p2[0] - p1[0])]
if orthog[0] == 0 and orthog[1] == 0:
return
scale = radius / (orthog[0] * orthog[0] + orthog[1] * orthog[1]) ** 0.5
orthog[0] = round(orthog[0] * scale)
orthog[1] = round(orthog[1] * scale)
points = [
(p1[0] - orthog[0], p1[1] - orthog[1]),
(p1[0] + orthog[0], p1[1] + orthog[1]),
(p2[0] + orthog[0], p2[1] + orthog[1]),
(p2[0] - orthog[0], p2[1] - orthog[1]),
]
pygame.draw.polygon(self.surface, fill_color.as_int(), points)
pygame.draw.circle(
self.surface,
fill_color.as_int(),
(round(p1[0]), round(p1[1])),
round(radius),
)
pygame.draw.circle(
self.surface,
fill_color.as_int(),
(round(p2[0]), round(p2[1])),
round(radius),
)
def draw_polygon(
self,
verts: Sequence[Tuple[float, float]],
radius: float,
outline_color: SpaceDebugColor,
fill_color: SpaceDebugColor,
) -> None:
ps = [to_pygame(v, self.surface) for v in verts]
ps += [ps[0]]
radius = 2
pygame.draw.polygon(self.surface, light_color(fill_color).as_int(), ps)
if radius > 0:
for i in range(len(verts)):
a = verts[i]
b = verts[(i + 1) % len(verts)]
self.draw_fat_segment(a, b, radius, fill_color, fill_color)
def draw_dot(self, size: float, pos: Tuple[float, float], color: SpaceDebugColor) -> None:
p = to_pygame(pos, self.surface)
pygame.draw.circle(self.surface, color.as_int(), p, round(size), 0)
def get_mouse_pos(surface: pygame.Surface) -> Tuple[int, int]:
"""Get position of the mouse pointer in pymunk coordinates."""
p = pygame.mouse.get_pos()
return from_pygame(p, surface)
def to_pygame(p: Tuple[float, float], surface: pygame.Surface) -> Tuple[int, int]:
"""Convenience method to convert pymunk coordinates to pygame surface
local coordinates.
Note that in case positive_y_is_up is False, this function won't actually do
anything except converting the point to integers.
"""
if positive_y_is_up:
return round(p[0]), surface.get_height() - round(p[1])
else:
return round(p[0]), round(p[1])
def from_pygame(p: Tuple[float, float], surface: pygame.Surface) -> Tuple[int, int]:
"""Convenience method to convert pygame surface local coordinates to
pymunk coordinates
"""
return to_pygame(p, surface)
def light_color(color: SpaceDebugColor):
color = np.minimum(1.2 * np.float32([color.r, color.g, color.b, color.a]), np.float32([255]))
color = SpaceDebugColor(r=color[0], g=color[1], b=color[2], a=color[3])
return color

24
poetry.lock generated
View File

@ -3096,6 +3096,25 @@ numpy = ">=1.14,<2"
docs = ["matplotlib", "numpydoc (==1.1.*)", "sphinx", "sphinx-book-theme", "sphinx-remove-toctrees"]
test = ["pytest", "pytest-cov"]
[[package]]
name = "sim-pusht"
version = "0.1.0"
description = "PushT environment for LeRobot"
optional = true
python-versions = "<4.0,>=3.10"
files = [
{file = "sim_pusht-0.1.0-py3-none-any.whl", hash = "sha256:1348dcab5ea8460eff2dc97b7d62dd40f2a382df92bfdc69ff5c0224900690b0"},
{file = "sim_pusht-0.1.0.tar.gz", hash = "sha256:d8f6a2207fd781348156206728329aa6338e9785cfc07679c5c48889b34d9b14"},
]
[package.dependencies]
gymnasium = ">=0.29.1,<0.30.0"
opencv-python = ">=4.9.0.80,<5.0.0.0"
pygame = ">=2.5.2,<3.0.0"
pymunk = ">=6.6.0,<7.0.0"
scikit-image = ">=0.22.0,<0.23.0"
shapely = ">=2.0.3,<3.0.0"
[[package]]
name = "six"
version = "1.16.0"
@ -3586,7 +3605,10 @@ files = [
docs = ["furo", "jaraco.packaging (>=9.3)", "jaraco.tidelift (>=1.4)", "rst.linker (>=1.9)", "sphinx (>=3.5)", "sphinx-lint"]
testing = ["big-O", "jaraco.functools", "jaraco.itertools", "more-itertools", "pytest (>=6)", "pytest-checkdocs (>=2.4)", "pytest-cov", "pytest-enabler (>=2.2)", "pytest-ignore-flaky", "pytest-mypy", "pytest-ruff (>=0.2.1)"]
[extras]
pusht = ["sim-pusht"]
[metadata]
lock-version = "2.0"
python-versions = "^3.10"
content-hash = "174c7d42f8039eedd2c447a4e6cae5169782cbd94346b5606572a0010194ca05"
content-hash = "91dcb5cc851e0a348bfa36801e6cd260391a851623f0949575a5a19ca014d75c"

View File

@ -1,19 +1,23 @@
[tool.poetry]
name = "lerobot"
version = "0.1.0"
description = "Le robot is learning"
description = "🤗 LeRobot: State-of-the-art Machine Learning for Real-World Robotics in Pytorch"
authors = [
"Rémi Cadène <re.cadene@gmail.com>",
]
maintainers = [
"Alexander Soare <alexander.soare159@gmail.com>",
"Simon Alibert <alibert.sim@gmail.com>",
]
repository = "https://github.com/Cadene/lerobot"
readme = "README.md"
license = "MIT"
license = "Apache-2.0"
keywords = ["robotics, deep, reinforcement, learning, pytorch"]
classifiers=[
"Development Status :: 3 - Alpha",
"Intended Audience :: Developers",
"Topic :: Software Development :: Build Tools",
"License :: OSI Approved :: MIT License",
"License :: OSI Approved :: Apache Software License",
"Programming Language :: Python :: 3.10",
]
packages = [{include = "lerobot"}]
@ -52,11 +56,19 @@ robomimic = "0.2.0"
gymnasium-robotics = "^1.2.4"
gymnasium = "^0.29.1"
cmake = "^3.29.0.1"
sim-pusht = { version = "^0.1.0", optional = true}
[tool.poetry.extras]
pusht = ["sim-pusht"]
[tool.poetry.group.dev.dependencies]
pre-commit = "^3.6.2"
debugpy = "^1.8.1"
[tool.poetry.group.test.dependencies]
pytest = "^8.1.0"
pytest-cov = "^5.0.0"
@ -93,6 +105,9 @@ exclude = [
select = ["E4", "E7", "E9", "F", "I", "N", "B", "C4", "SIM"]
ignore-init-module-imports = true
[tool.ruff.lint.isort]
known-first-party = ["pusht"]
[tool.poetry-dynamic-versioning]
enable = true