def infer(self, images: List[OrthographicImage], method: SelectionMethod,
**params) -> List[Action]:
if self.monte_carlo: # Adapt monte carlo progress parameter s
epoch_in_collection = Loader.get_episode_count(Config.collection)
s_not_bounded = (epoch_in_collection - 3500) * 1 / (4500 - 3500)
self.inference.current_s = max(min(s_not_bounded, 1.0), 0.0)
self.check_for_model_reload()
if len(images) == 3:
images[2].mat = images[2].mat[:, :, ::-1] # BGR to RGB
action = self.inference.infer(images, method)
self.indexer.to_action(action)
print(action, method)
estimated_reward_lower_than_threshold = action.estimated_reward < Config.bin_empty_at_max_probability
bin_empty = estimated_reward_lower_than_threshold and Epoch.selection_method_should_be_high(
method)
if bin_empty:
return [Action('bin_empty', safe=1)]
self.converter.calculate_pose(action, images)
return [action]
def infer(self, images: List[OrthographicImage],
method: SelectionMethod) -> Action:
if self.monte_carlo: # Adapt monte carlo progress parameter s
epoch_in_database = Loader.get_episode_count(Config.grasp_database)
s_not_bounded = (epoch_in_database - 3500) * 1 / (4500 - 3500)
self.inference.current_s = max(min(s_not_bounded, 1.0), 0.0)
current_model_st_mtime = Loader.get_model_path(
self.model).stat().st_mtime
if self.watch_for_model_modification and current_model_st_mtime > self.model_last_modified + 0.5: # [s]
logger.warning(f'Reload model {self.model}.')
try:
self.inference.model = Loader.get_model(
self.model, output_layer=self.output_layer)
self.model_last_modified = Loader.get_model_path(
self.model).stat().st_mtime
except OSError:
logger.info('Could not load model, probabily file locked.')
if len(images) == 3:
images[2].mat = images[2].mat[:, :, ::-1] # BGR to RGB
action = self.inference.infer(images, method)
self.indexer.to_action(action)
estimated_reward_lower_than_threshold = action.estimated_reward < Config.bin_empty_at_max_probability
bin_empty = estimated_reward_lower_than_threshold and Epoch.selection_method_should_be_high(
method)
if bin_empty:
return Action('bin_empty', safe=1)
self.converter.calculate_pose(action, images)
return action
from collections import defaultdict
from data.loader import Loader
database_list = Loader.get_databases()
total_count = sum(Loader.get_episode_count(d) for d in database_list)
print(f'Total count {total_count}')
recordings_on_date = defaultdict(lambda: 0)
image_count = 0
for d in database_list:
for _, e in Loader.yield_episodes(d):
data = e['id'].split('-')
date = f'{data[0]}-{data[1]}' # -{data[2]}'
recordings_on_date[date] += 1
image_count += len(e['actions'][0]['images'])
print(f'Total image count {image_count}')
for m in sorted(recordings_on_date):
print(f'{m}: {recordings_on_date[m]}')