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CARLA cleanups + calculating the distance to goal

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itaicaspi-intel
2018-09-16 16:37:04 +03:00
parent 6797824892
commit bb76c5c726
3 changed files with 8 additions and 7 deletions
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4
.gitignore vendored
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@@ -21,3 +21,7 @@ contrib
test_log_* test_log_*
dist dist
datasets datasets
.cache
.pytest_cache
core
trace_test*

5
rl_coach/environments/carla_environment.py
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@@ -359,6 +359,9 @@ class CarlaEnvironment(Environment):
measurements.player_measurements.transform.location.y, measurements.player_measurements.transform.location.y,
measurements.player_measurements.transform.location.z] measurements.player_measurements.transform.location.z]
self.distance_from_goal = np.linalg.norm(np.array(self.location[:2]) -
[self.current_goal.location.x, self.current_goal.location.y])
is_collision = measurements.player_measurements.collision_vehicles != 0 \ is_collision = measurements.player_measurements.collision_vehicles != 0 \
or measurements.player_measurements.collision_pedestrians != 0 \ or measurements.player_measurements.collision_pedestrians != 0 \
or measurements.player_measurements.collision_other != 0 or measurements.player_measurements.collision_other != 0
@@ -381,8 +384,6 @@ class CarlaEnvironment(Environment):
self.state['high_level_command'] = directions self.state['high_level_command'] = directions
if (measurements.game_timestamp >= self.episode_max_time) or is_collision: if (measurements.game_timestamp >= self.episode_max_time) or is_collision:
# screen.success('EPISODE IS DONE. GameTime: {}, Collision: {}'.format(str(measurements.game_timestamp),
# str(is_collision)))
self.done = True self.done = True
self.state['measurements'] = np.array(self.measurements) self.state['measurements'] = np.array(self.measurements)

6
rl_coach/utilities/carla_dataset_to_replay_buffer.py
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@@ -71,10 +71,6 @@ def create_dataset(dataset_root, output_path):
observations = train_set['rgb'][:] # forward camera observations = train_set['rgb'][:] # forward camera
measurements = np.expand_dims(train_set['targets'][:, 10], -1) # forward speed measurements = np.expand_dims(train_set['targets'][:, 10], -1) # forward speed
actions = train_set['targets'][:, :3] # steer, gas, brake actions = train_set['targets'][:, :3] # steer, gas, brake
# actions[:, :2] = actions[:, 1:3]
# actions[:, 2] = train_set['targets'][:, 0] # gas, brake, steer
# actions[:, 1] -= actions[:, 2]
# actions = actions[:, :2][:, ::-1]
high_level_commands = train_set['targets'][:, 24].astype('int') - 2 # follow lane, left, right, straight high_level_commands = train_set['targets'][:, 24].astype('int') - 2 # follow lane, left, right, straight
@@ -104,4 +100,4 @@ if __name__ == "__main__":
default='carla_train_set_replay_buffer.p') default='carla_train_set_replay_buffer.p')
args = argparser.parse_args() args = argparser.parse_args()
create_dataset(args.dataset_root, args.output_path) create_dataset(args.dataset_root, args.output_path)