An experiment tracking library built on top of pybag.
output_dir is a directory. The logger writes to <output_dir>/<YYYYMMDD_HHMMSS_microseconds>_<logger-name>.mcap.
from track import Logger
logger = Logger("demo", output_dir="logs").open()
logger.info("training started")
logger.warning("learning rate is high")
logger.close()import numpy as np
from track import Logger
image = np.zeros((64, 64, 3), dtype=np.uint8)
image[:, :, 1] = 255 # green
logger = Logger("demo", output_dir="logs").open()
logger.log_image("camera/rgb", image, format="png")
logger.close()import numpy as np
from track import Logger
dtype = np.dtype([("x", "f4"), ("y", "f4"), ("z", "f4")])
points = np.zeros(3, dtype=dtype)
points["x"] = [0.0, 1.0, 0.0]
points["y"] = [0.0, 0.0, 1.0]
points["z"] = [0.0, 0.0, 0.0]
logger = Logger("demo", output_dir="logs").open()
logger.log_pointcloud("lidar", points)
logger.close()from track import Logger
logger = Logger("demo", output_dir="logs").open()
logger.add_metadata("experiment", {"name": "baseline", "epoch": "1"})
logger.add_attachment(
"config.json",
b'{"batch_size": 32}',
media_type="application/json",
)
logger.close()