def load_from_csv(self, csv_file, reset_save_required=True):
# type: (File [r], Optional[bool] -> int
""" Load From CSV: Loads all metrics stored in a CSV file into the StatsManager instance.
Arguments:
csv_file: A file handle opened in read mode (e.g. open('...', 'r')).
reset_save_required: If True, clears the flag indicating that a save is required.
Returns:
int or None: Number of frames/rows read from the CSV file, or None if the
input file was blank.
Raises:
StatsFileCorrupt: Stats file is corrupt and can't be loaded, or wrong file
was specified.
"""
csv_reader = get_csv_reader(csv_file)
num_cols = None
num_metrics = None
num_frames = None
# First Row: Frame Num, Timecode, [metrics...]
try:
row = next(csv_reader)
# Backwards compatibility for previous versions of statsfile
# which included an additional header row.
if not self.valid_header(row):
row = next(csv_reader)
except StopIteration:
# If the file is blank or we couldn't decode anything, assume the file was empty.
return None
if not self.valid_header(row):
raise StatsFileCorrupt()
num_cols = len(row)
num_metrics = num_cols - 2
if not num_metrics > 0:
raise StatsFileCorrupt('No metrics defined in CSV file.')
self._loaded_metrics = row[2:]
num_frames = 0
for row in csv_reader:
metric_dict = {}
if not len(row) == num_cols:
raise StatsFileCorrupt(
'Wrong number of columns detected in stats file row.')
for i, metric_str in enumerate(row[2:]):
if metric_str and metric_str != 'None':
try:
metric_dict[self._loaded_metrics[i]] = float(
metric_str)
except ValueError:
raise StatsFileCorrupt(
'Corrupted value in stats file: %s' % metric_str)
self.set_metrics(int(row[0]), metric_dict)
num_frames += 1
logger.info('Loaded %d metrics for %d frames.', num_metrics,
num_frames)
if reset_save_required:
self._metrics_updated = False
return num_frames
def test_load_empty_stats():
""" Test loading an empty stats file, ensuring it results in no errors. """
open(TEST_STATS_FILES[0], 'w').close()
with open(TEST_STATS_FILES[0], 'r') as stats_file:
stats_manager = StatsManager()
stats_reader = get_csv_reader(stats_file)
stats_manager.load_from_csv(stats_reader)
def test_load_empty_stats(test_video_file):
""" Test loading an empty stats file, ensuring it results in no errors. """
try:
stats_file = open(TEST_STATS_FILES[0], 'w')
stats_file.close()
stats_file = open(TEST_STATS_FILES[0], 'r')
stats_manager = StatsManager()
stats_reader = get_csv_reader(stats_file)
stats_manager.load_from_csv(stats_reader)
finally:
stats_file.close()
os.remove(TEST_STATS_FILES[0])
def test_load_empty_stats(test_video_file):
""" Test loading an empty stats file, ensuring it results in no errors. """
try:
stats_file = open(TEST_STATS_FILES[0], 'w')
stats_file.close()
stats_file = open(TEST_STATS_FILES[0], 'r')
stats_manager = StatsManager()
stats_reader = get_csv_reader(stats_file)
stats_manager.load_from_csv(stats_reader)
finally:
stats_file.close()
os.remove(TEST_STATS_FILES[0])
def load_from_csv(self,
csv_file,
base_timecode=None,
reset_save_required=True):
# type: (File [r], FrameTimecode, Optional[bool] -> int
""" Load From CSV: Loads all metrics stored in a CSV file into the StatsManager instance.
Arguments:
csv_file: A file handle opened in read mode (e.g. open('...', 'r')).
base_timecode: The base_timecode obtained from the frame source VideoManager.
If using an OpenCV VideoCapture, create one using the video framerate by
setting base_timecode=FrameTimecode(0, fps=video_framerate).
If base_timecode is not set (i.e. is None), the framerate is not validated.
reset_save_required: If True, clears the flag indicating that a save is required.
Returns:
int or None: Number of frames/rows read from the CSV file, or None if the
input file was blank.
Raises:
StatsFileCorrupt: Stats file is corrupt and can't be loaded, or wrong file
was specified.
StatsFileFramerateMismatch: Framerate does not match the loaded stats file,
indicating either the wrong video or wrong stats file was specified.
"""
csv_reader = get_csv_reader(csv_file)
num_cols = None
num_metrics = None
num_frames = None
# First row: Framerate, [video_framerate]
try:
row = next(csv_reader)
except StopIteration:
# If the file is blank or we couldn't decode anything, assume the file was empty.
return num_frames
# First Row (FPS = [...]) and ensure framerate equals base_timecode if set.
if not len(row) == 2 or not row[0] == COLUMN_NAME_FPS:
raise StatsFileCorrupt()
stats_file_framerate = float(row[1])
if stats_file_framerate < MINIMUM_FRAMES_PER_SECOND_FLOAT:
raise StatsFileCorrupt(
"Invalid framerate detected in CSV stats file "
"(decoded FPS: %f)." % stats_file_framerate)
if base_timecode is not None and not base_timecode.equal_framerate(
stats_file_framerate):
raise StatsFileFramerateMismatch(base_timecode.get_framerate(),
stats_file_framerate)
# Second Row: Frame Num, Timecode, [metrics...]
try:
row = next(csv_reader)
except StopIteration:
raise StatsFileCorrupt("Header row(s) missing.")
if not row or not len(row) >= 2:
raise StatsFileCorrupt()
if row[0] != COLUMN_NAME_FRAME_NUMBER or row[1] != COLUMN_NAME_TIMECODE:
raise StatsFileCorrupt()
num_cols = len(row)
num_metrics = num_cols - 2
if not num_metrics > 0:
raise StatsFileCorrupt('No metrics defined in CSV file.')
metric_keys = row[2:]
num_frames = 0
for row in csv_reader:
metric_dict = {}
if not len(row) == num_cols:
raise StatsFileCorrupt(
'Wrong number of columns detected in stats file row.')
for i, metric_str in enumerate(row[2:]):
if metric_str and metric_str != 'None':
try:
metric_dict[metric_keys[i]] = float(metric_str)
except ValueError:
raise StatsFileCorrupt(
'Corrupted value in stats file: %s' % metric_str)
self.set_metrics(int(row[0]), metric_dict)
num_frames += 1
logging.info('Loaded %d metrics for %d frames.', num_metrics,
num_frames)
if reset_save_required:
self._metrics_updated = False
return num_frames
def load_from_csv(self, csv_file, base_timecode=None, reset_save_required=True):
# type: (File [r], FrameTimecode, Optional[bool] -> int
""" Load From CSV: Loads all metrics stored in a CSV file into the StatsManager instance.
Arguments:
csv_file: A file handle opened in read mode (e.g. open('...', 'r')).
base_timecode: The base_timecode obtained from the frame source VideoManager.
If using an OpenCV VideoCapture, create one using the video framerate by
setting base_timecode=FrameTimecode(0, fps=video_framerate).
If base_timecode is not set (i.e. is None), the framerate is not validated.
reset_save_required: If True, clears the flag indicating that a save is required.
Returns:
int or None: Number of frames/rows read from the CSV file, or None if the
input file was blank.
Raises:
StatsFileCorrupt: Stats file is corrupt and can't be loaded, or wrong file
was specified.
StatsFileFramerateMismatch: Framerate does not match the loaded stats file,
indicating either the wrong video or wrong stats file was specified.
"""
csv_reader = get_csv_reader(csv_file)
num_cols = None
num_metrics = None
num_frames = None
# First row: Framerate, [video_framerate]
try:
row = next(csv_reader)
except StopIteration:
# If the file is blank or we couldn't decode anything, assume the file was empty.
return num_frames
# First Row (FPS = [...]) and ensure framerate equals base_timecode if set.
if not len(row) == 2 or not row[0] == COLUMN_NAME_FPS:
raise StatsFileCorrupt()
stats_file_framerate = float(row[1])
if stats_file_framerate < MINIMUM_FRAMES_PER_SECOND_FLOAT:
raise StatsFileCorrupt("Invalid framerate detected in CSV stats file "
"(decoded FPS: %f)." % stats_file_framerate)
if base_timecode is not None and not base_timecode.equal_framerate(stats_file_framerate):
raise StatsFileFramerateMismatch(base_timecode.get_framerate(), stats_file_framerate)
# Second Row: Frame Num, Timecode, [metrics...]
try:
row = next(csv_reader)
except StopIteration:
raise StatsFileCorrupt("Header row(s) missing.")
if not row or not len(row) >= 2:
raise StatsFileCorrupt()
if row[0] != COLUMN_NAME_FRAME_NUMBER or row[1] != COLUMN_NAME_TIMECODE:
raise StatsFileCorrupt()
num_cols = len(row)
num_metrics = num_cols - 2
if not num_metrics > 0:
raise StatsFileCorrupt('No metrics defined in CSV file.')
metric_keys = row[2:]
num_frames = 0
for row in csv_reader:
metric_dict = {}
if not len(row) == num_cols:
raise StatsFileCorrupt('Wrong number of columns detected in stats file row.')
for i, metric_str in enumerate(row[2:]):
if metric_str and metric_str != 'None':
try:
metric_dict[metric_keys[i]] = float(metric_str)
except ValueError:
raise StatsFileCorrupt('Corrupted value in stats file: %s' % metric_str)
self.set_metrics(int(row[0]), metric_dict)
num_frames += 1
logging.info('Loaded %d metrics for %d frames.', num_metrics, num_frames)
if reset_save_required:
self._metrics_updated = False
return num_frames
def load_from_csv(self,
csv_file,
base_timecode=None,
reset_save_required=True):
# type: (File [r], Optional[FrameTimecode]) -> int
csv_reader = get_csv_reader(csv_file)
num_cols = None
num_metrics = None
num_frames = None
# First row: Framerate, [video_framerate]
try:
row = next(csv_reader)
except StopIteration:
# If the file is blank or we couldn't decode anything, assume the file was empty.
return
# First Row (FPS = [...]) and ensure framerate equals base_timecode if set.
if not len(row) == 2 or not row[0] == COLUMN_NAME_FPS:
raise StatsFileCorrupt()
stats_file_framerate = float(row[1])
if stats_file_framerate < MINIMUM_FRAMES_PER_SECOND_FLOAT:
raise StatsFileCorrupt(
"Invalid framerate detected in CSV stats file "
"(decoded FPS: %f)." % stats_file_framerate)
if base_timecode is not None and not base_timecode.equal_framerate(
stats_file_framerate):
raise StatsFileFramerateMismatch(base_timecode.get_framerate(),
stats_file_framerate)
# Second Row: Frame Num, Timecode, [metrics...]
try:
row = next(csv_reader)
except StopIteration:
raise StatsFileCorrupt("Header row(s) missing.")
if not row or not len(row) >= 2:
raise StatsFileCorrupt()
if row[0] != COLUMN_NAME_FRAME_NUMBER or row[1] != COLUMN_NAME_TIMECODE:
raise StatsFileCorrupt()
num_cols = len(row)
num_metrics = num_cols - 2
if not num_metrics > 0:
raise StatsFileCorrupt('No metrics defined in CSV file.')
metric_keys = row[2:]
num_frames = 0
for row in csv_reader:
metric_dict = {}
if not len(row) == num_cols:
raise StatsFileCorrupt(
'Wrong number of columns detected in stats file row.')
for i, metric_str in enumerate(row[2:]):
if metric_str and metric_str != 'None':
try:
metric_dict[metric_keys[i]] = float(metric_str)
except ValueError:
raise StatsFileCorrupt(
'Corrupted value in stats file: %s' % metric_str)
self.set_metrics(int(row[0]), metric_dict)
num_frames += 1
logging.info('Loaded %d metrics for %d frames.', num_metrics,
num_frames)
if reset_save_required:
self._metrics_updated = False
return num_frames