def combined_json(
detection_json_dir,
classification_json_dir):
""" Combine results from detector and classifier
@param detection_json_dir: directory to detector results
@param classification_json_dir: directory to classifier results
"""
for json_file in tools.find_files(detection_json_dir):
json_data = data.parse_json(json_file)
annotations = json_data['annotations']
for i in range(len(annotations)):
classification_json_file = os.path.join(
classification_json_dir,
os.path.basename(json_file).split('.')[0]
+ '_' + str(i) + '.json')
if os.path.exists(classification_json_file):
classification_annotations = data.parse_json(
classification_json_file)['annotations'][0]
annotations[i]['type'] = 'detection_classification'
annotations[i]['label'] += '_' + \
classification_annotations['label']
annotations[i]['labinfo'] = classification_annotations[
'labinfo']
json_data['annotations'] = annotations
out_json = os.path.join(
os.path.dirname(json_file),
os.path.basename(json_file).split('.')[0] + '_combined.json')
with open(out_json, 'w') as wf:
json.dump(json_data, wf)
def set_dyda_config(self, dyda_config, encoding=None,
terminate_if_fail=True):
""" Set TrainerBase.config
:param str dyda_config: Input for setting up config.It can be a
read dictionary or a path of the config json
:param str encoding: Choose encoding of the config json file
:param bool terminate_if_fail: True to terminate the programe if the
setting of TrainerBase.config fails.
:return: None
:rtype: None
"""
if isinstance(dyda_config, dict):
self.config = dyda_config
self.base_logger.info('TrainerBase.config set successfully')
elif os.path.isfile(dyda_config):
try:
self.config = data.parse_json(
dyda_config, encoding=encoding
)
except IOError:
self.base_logger.error('Cannot open %s' % dyda_config)
if terminate_if_fail:
sys.exit(0)
except Exception:
traceback.print_exc(file=sys.stdout)
if terminate_if_fail:
sys.exit(0)
def reverse_padding(
in_json,
shift,
size,
padded_dir,
frame_dir):
""" Reverse detection result of padded image
to detection result fo original image
@param in_json: input json filename
@param shift: (shift_x, shift_y)
@param size: (width, height), size of original image
@param padded_dir: directory of padded images
@param frame_dir: directory of original images
"""
shift_x = shift[0]
shift_y = shift[1]
width = size[0]
height = size[1]
json_data = data.parse_json(in_json)
if json_data['folder'] == padded_dir:
json_data = shift_boxes(json_data, (shift_x, shift_y), (width, height))
json_data['folder'] = frame_dir
with open(in_json, 'w') as wf:
json.dump(json_data, wf)
def get_metadata(self, metadata_input, encoding=None):
"""
Read from metadata_input
@param metadata_input: filepath of the dict of metadata
Keyword arguments:
encoding -- encoding of the json file
"""
metadata = {}
if isinstance(metadata_input, dict):
metadata = metadata_input
return metadata
elif os.path.isfile(metadata_input):
try:
metadata = data.parse_json(metadata_input, encoding=encoding)
return metadata
except IOError:
print('[dyda] Error: cannot open %s' % metadata_input)
self.terminate_flag = True
return {}
except Exception:
traceback.print_exc(file=sys.stdout)
self.terminate_flag = True
return {}
else:
self.terminate_flag = True
print("%s is not a valid file" % metadata_input)
return {}
def replace_dyda_config(self, dyda_config, session,
encoding=None, terminate_if_fail=True):
""" Replace the whole TrainerBase.config or just partially
:param str dyda_config: Input for setting up config.It can be a
read dictionary or a path of the config json
:param str session: Specify the component session, all for all sessions
:param str encoding: Choose encoding of the config json file
:param bool terminate_if_fail: True to terminate the programe if the
setting of TrainerBase.config fails.
:return: None
:rtype: None
"""
if session == 'all':
self.set_dyda_config(
dyda_config, encoding=encoding,
terminate_if_fail=terminate_if_fail
)
else:
config = None
if isinstance(dyda_config, dict):
config = dyda_config
elif os.path.isfile(dyda_config):
try:
config = data.parse_json(
dyda_config, encoding=encoding
)
except IOError:
self.base_logger.error('Cannot open %s' % dyda_config)
if terminate_if_fail:
sys.exit(0)
except Exception:
traceback.print_exc(file=sys.stdout)
if terminate_if_fail:
sys.exit(0)
if config:
if session in config.keys():
self.config[session] = config[session]
else:
if isinstance(dyda_config, dict):
self.base_logger.warning('%s session not found in '
'input dyda_config dict'
% session)
elif isinstance(dyda_config, str):
self.base_logger.warning('%s session not found in %s'
% (session, dyda_config))
else:
self.base_logger.warning('%s session not found'
% session)
def box_append(
filename,
annotations):
""" Append annotations to the file
@param filename: filename of the file appended
@param annotations: annotations of a detection result
"""
if os.path.isfile(filename):
base = data.parse_json(filename)
else:
base = []
for i in range(len(annotations)):
base.append(annotations[i])
data.write_json(base, filename)
def conv_to_df(array, ffields=None, target=None):
"""Convert array to pandas.DataFrame
@param array: input array to be converted
Keyword arguments:
ffields -- json file of the fields (default: None)
target -- if ffields is specified, can also specified
the target column to be used (default: None)
"""
if ffields is not None:
fields = data.parse_json(ffields)
if isinstance(target, int):
print('[pandas_data] Converting field from %s to target' %
fields[target])
fields[target] = 'target'
return pd.DataFrame(array, columns=fields)
return pd.DataFrame(array)