Closed williamhoole closed 6 months ago
Of course it is. You will need to change the config file to refer to the new annotation file, by changing the 'data' var in the config.
for example:
data = dict(
samples_per_gpu=16,
workers_per_gpu=8,
train=dict(
type='TransformerPoseDataset',
ann_file=f'NEW_ANNOTATION.json',
img_prefix=f'{NEW_IMAGE_ROOT/',
# img_prefix=f'{data_root}',
data_cfg=data_cfg,
valid_class_ids=None,
max_kpt_num=channel_cfg['max_kpt_num'],
num_shots=1,
pipeline=train_pipeline),
Keep in mind the new annotation should have similar structure as the original MP100 dataset annotation.
Is it possible to train/ fine tune the model on a custom dataset?