Customising Video Renders¶
Tweaking Video Rendering Settings¶
TorchRL relies heavily on the torchvision.io and PyAV modules for its video logging capabilities. Though these libraries are quite convenient and powerful, it is not easy to access the variety of knobs and settings at your disposal.
This guide hopes to clarify what appear to be the general principles behind customising video rendering, and show you how you can manually adjust your rollouts’ rendering settings to your liking.
General Principles¶
Ultimately, torchvision.io and PyAV make calls to FFmpeg libraries in order to render videos.
In other words:
Whatever can be fed into FFmpeg, we can also feed into TorchRL’s
Loggers.For any custom settings we wish to use, we must reference them from FFmpeg’s documentation
Video Rendering Customization Example¶
Suppose the following snippet gave us extremely blurry videos, even though we provided it clear, frame-by-frame images to stitch together:
from torchrl.envs import GymEnv, TransformedEnv
from torchrl.record import CSVLogger, VideoRecorder
logger = CSVLogger(exp_name="my_exp")
env = GymEnv("CartPole-v1", from_pixels=True, pixels_only=False)
recorder = VideoRecorder(logger, tag="my_video")
record_env = TransformedEnv(env, recorder)
rollout = record_env.rollout(max_steps=3)
recorder.dump()
Since TorchRL’s default video codec is H264, the settings that we must change should be in there.
For the purposes of this example, let us choose a
Constant Rate Factor (CRF) of
17 and a preset of slow,
as advised by the documentation.
We can improve the video quality by appending all our desired settings
(as keyword arguments) to recorder like so:
recorder = VideoRecorder(logger, tag = "my_video", options = {"crf": "17", "preset": "slow"})
