def main():
"""Main entry point for running sg-prototype."""
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
output = {}
# YOUR STUFF GOES HERE
output.update({"input_parameters": mod.args})
if "output_json" in mod.args:
mod.output(output)
else:
print(mod.get_output_json(output))
def main():
"""Main entry point for running AllenSDK Eye Tracking."""
try:
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
istream = CvInputStream(mod.args["input_source"])
ostream = setup_annotation(
istream.frame_shape,
**mod.args.get("annotation", DEFAULT_ANNOTATION))
qc_params = mod.args.get("qc", {})
generate_plots = qc_params.get("generate_plots",
EyeTracker.DEFAULT_GENERATE_QC_OUTPUT)
tracker = EyeTracker(istream, ostream, mod.args.get("starburst", {}),
mod.args.get("ransac",
{}), mod.args["pupil_bounding_box"],
mod.args["cr_bounding_box"], generate_plots,
**mod.args.get("eye_params", {}))
cr_params, pupil_params, cr_err, pupil_err = tracker.process_stream(
start=mod.args.get("start_frame", 0),
stop=mod.args.get("stop_frame", None),
step=mod.args.get("frame_step", 1))
output = write_output(mod.args["output_dir"], cr_params, pupil_params,
tracker.mean_frame)
pupil_intensity = None
if tracker.adaptive_pupil:
pupil_intensity = tracker.pupil_colors
if generate_plots:
write_QC_output(tracker.annotator,
cr_params,
pupil_params,
cr_err,
pupil_err,
tracker.mean_frame,
pupil_intensity=pupil_intensity,
**mod.args)
output["input_parameters"] = mod.args
if "output_json" in mod.args:
mod.output(output, indent=1)
else:
print(json.dumps(mod.get_output_json(output), indent=1))
except marshmallow.ValidationError as e:
print(e)
argparser = schema_argparser(InputParameters())
argparser.print_usage()
def main():
from ._schemas import InputParameters, OutputParameters
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
output = calculate_quality_metrics(mod.args)
output.update({"input_parameters": mod.args})
if "output_json" in mod.args:
mod.output(output, indent=2)
else:
print(mod.get_output_json(output))
def main():
from ._schemas import InputParameters, OutputParameters
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
output = classify_noise_templates(mod.args)
output.update({"input_parameters": mod.args})
if "output_json" in mod.args:
mod.output(output, indent=2)
else:
print(mod.get_output_json(output))
def main():
from ._schemas import InputParameters, OutputParameters
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
# output = calculate_stimulus_metrics_ondisk(mod.args)
output = calculate_stimulus_metrics_gather(mod.args)
if MPI_rank == 0:
output.update({"input_parameters": mod.args})
if "output_json" in mod.args:
mod.output(output, indent=2)
else:
log_info(mod.get_output_json(output))
barrier()
def main():
from ._schemas import InputParameters, OutputParameters
"""Main entry point:"""
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
output = get_psth_events(mod.args)
output.update({"input_parameters": mod.args})
if "output_json" in mod.args:
mod.output(output, indent=2)
else:
print(mod.get_output_json(output))
def main():
from ._schemas import InputParameters, OutputParameters
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
output = run_automerging(mod.args)
output.update({"input_parameters": mod.args})
if "output_json" in mod.args:
mod.output(output, indent=2)
else:
print(mod.get_output_json(output))
def main():
from ._schemas import InputParameters, OutputParameters
"""Main entry point:"""
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
if mod.args['tPrime_helper_params']['tPrime_3A']:
output = call_TPrime_3A(mod.args)
else:
output = call_TPrime(mod.args)
output.update({"input_parameters": mod.args})
if "output_json" in mod.args:
mod.output(output, indent=2)
else:
print(mod.get_output_json(output))
def main():
"""Main entry point for running AllenSDK Eye Tracking."""
try:
mod = ArgSchemaParser(schema_type=InputParameters,
output_schema_type=OutputParameters)
starburst_args = get_starburst_args(mod.args["starburst"])
istream = CvInputStream(mod.args["input_source"])
im_shape = istream.frame_shape
ostream = setup_annotation(im_shape, **mod.args["annotation"])
tracker = EyeTracker(im_shape, istream, ostream, starburst_args,
mod.args["ransac"],
mod.args["pupil_bounding_box"],
mod.args["cr_bounding_box"],
mod.args["qc"]["generate_plots"],
**mod.args["eye_params"])
pupil_parameters, cr_parameters = tracker.process_stream(
start=mod.args.get("start_frame", 0),
stop=mod.args.get("stop_frame", None),
step=mod.args.get("frame_step", 1))
output = write_output(mod.args["output_dir"], cr_parameters,
pupil_parameters, tracker.mean_frame)
if mod.args["qc"]["generate_plots"]:
write_QC_output(tracker.annotator, cr_parameters, pupil_parameters,
tracker.mean_frame, **mod.args)
output["input_parameters"] = mod.args
if "output_json" in mod.args:
mod.output(output, indent=1)
else:
print(json.dumps(mod.get_output_json(output), indent=1))
except marshmallow.ValidationError as e:
print(e)
argparser = schema_argparser(InputParameters())
argparser.print_usage()
