mmcv/docs/utils.md

Utils

Config

Config class is used for manipulating config and config files. It supports loading configs from multiple file formats including python scripts, json file and yaml file. It provides dict-like apis to get and set values.

Here is an example of the config file test.py.

a = 1
b = {'b1': [0, 1, 2], 'b2': None}
c = (1, 2)
d = 'string'

To load and use configs

cfg = Config.fromfile('test.py')
assert cfg.a == 1
assert cfg.b.b1 == [0, 1, 2]
cfg.c = None
assert cfg.c == None

ProgressBar

If you want to apply a method to a list of items and track the progress, track_progress is a good choice. It will display a progress bar to tell the progress and ETA.

import mmcv

def func(item):
    # do something
    pass

tasks = [item_1, item_2, ..., item_n]

mmcv.track_progress(func, tasks)

The output is like the following.

There is another method track_parallel_progress, which wraps multiprocessing and progress visualization.

mmcv.track_parallel_progress(func, tasks, 8)  # 8 workers

Timer

It is convinient to compute the runtime of a code block with Timer.

import time

with mmcv.Timer():
    # simulate some code block
    time.sleep(1)

or try with since_start() and since_last_check(). This former can return the runtime since the timer starts and the latter will return the time since the last time checked.

timer = mmcv.Timer()
# code block 1 here
print(timer.since_start())
# code block 2 here
print(timer.since_last_check())
print(timer.since_start())