Inference and Testing¶
This section describes how to use the trained models for testing using a test set or running inference for any given videos.
To test using our trained models, download the required checkpoint, config, and dataset metadata from the Models section.
Computing accuracy using test set¶
Add a key called
pretrained
to the first line of the config, pointing to the.ckpt
pathAdd a sub-section called
test_pipeline
to thedata
section of the config.This section is of same format as
valid_pipeline
section.Finally, run the following snippet to compute accuracy for the given pose test set:
import omegaconf
from openhands.apis.inference import InferenceModel
cfg = omegaconf.OmegaConf.load("path/to/config.yaml")
model = InferenceModel(cfg=cfg)
model.init_from_checkpoint_if_available()
if cfg.data.test_pipeline.dataset.inference_mode:
model.test_inference()
else:
model.compute_test_accuracy()
Predicting for any given videos¶
In the same config as described above, just change the
root_dir
to point to any desired folder containing videos (or pose files)Set an additional variable called
inference_mode
astrue
, to indicate that there will be no ground truth.You can now run the inference using the same snippet above.