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# coding=utf-8
# Copyright 2021 The Google Research Authors.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
# Lint as: python3
"""A wrapper for dm_control environments which applies color distractions."""
from dm_control.rl import control
import numpy as np
class DistractingColorEnv(control.Environment):
"""Environment wrapper for color visual distraction.
**NOTE**: This wrapper should be applied BEFORE the pixel wrapper to make sure
the color changes are applied before rendering occurs.
"""
def __init__(self,
env,
step_std,
max_delta,
seed=None,
fixed=False,
):
"""Initialize the environment wrapper.
Args:
env: instance of dm_control Environment to wrap with augmentations.
"""
if step_std < 0:
raise ValueError("`step_std` must be greater than or equal to 0.")
if max_delta < 0:
raise ValueError("`max_delta` must be greater than or equal to 0.")
self._env = env
self._step_std = step_std
self._max_delta = max_delta
self._random_state = np.random.RandomState(seed=seed)
self._cam_type = None
self._current_rgb = None
self._max_rgb = None
self._min_rgb = None
self._original_rgb = None
self.fixed = fixed
self.first_reset = False
def reset(self):
"""Reset the distractions state."""
time_step = self._env.reset()
if not self.fixed or not self.first_reset:
self._reset_color()
self.first_reset = True
return time_step
def _reset_color(self):
# Save all original colors.
if self._original_rgb is None:
self._original_rgb = np.copy(self._env.physics.model.mat_rgba)[:, :3]
# Determine minimum and maximum rgb values.
self._max_rgb = np.clip(self._original_rgb + self._max_delta, 0.0, 1.0)
self._min_rgb = np.clip(self._original_rgb - self._max_delta, 0.0, 1.0)
# Pick random colors in the allowed ranges.
r = self._random_state.uniform(size=self._min_rgb.shape)
self._current_rgb = self._min_rgb + r * (self._max_rgb - self._min_rgb)
# Apply the color changes.
self._env.physics.model.mat_rgba[:, :3] = self._current_rgb
def step(self, action):
time_step = self._env.step(action)
if time_step.first():
self._reset_color()
return time_step
color_change = self._random_state.randn(*self._current_rgb.shape)
color_change = color_change * self._step_std
new_color = self._current_rgb + color_change
self._current_rgb = np.clip(
new_color,
a_min=self._min_rgb,
a_max=self._max_rgb,
)
# Apply the color changes.
self._env.physics.model.mat_rgba[:, :3] = self._current_rgb
return time_step
# Forward property and method calls to self._env.
def __getattr__(self, attr):
if hasattr(self._env, attr):
return getattr(self._env, attr)
raise AttributeError("'{}' object has no attribute '{}'".format(
type(self).__name__, attr))
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