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import os
import logging
import warnings
from video_llama.common.registry import registry
from video_llama.datasets.builders.base_dataset_builder import BaseDatasetBuilder
from video_llama.datasets.datasets.laion_dataset import LaionDataset
from video_llama.datasets.datasets.cc_sbu_dataset import CCSBUDataset, CCSBUAlignDataset
@registry.register_builder("cc_sbu")
class CCSBUBuilder(BaseDatasetBuilder):
train_dataset_cls = CCSBUDataset
DATASET_CONFIG_DICT = {"default": "configs/datasets/cc_sbu/defaults.yaml"}
def _download_ann(self):
pass
def _download_vis(self):
pass
def build(self):
self.build_processors()
build_info = self.config.build_info
datasets = dict()
split = "train"
# create datasets
# [NOTE] return inner_datasets (wds.DataPipeline)
dataset_cls = self.train_dataset_cls
datasets[split] = dataset_cls(
vis_processor=self.vis_processors[split],
text_processor=self.text_processors[split],
location=build_info.storage,
).inner_dataset
return datasets
@registry.register_builder("laion")
class LaionBuilder(BaseDatasetBuilder):
train_dataset_cls = LaionDataset
DATASET_CONFIG_DICT = {"default": "configs/datasets/laion/defaults.yaml"}
def _download_ann(self):
pass
def _download_vis(self):
pass
def build(self):
self.build_processors()
build_info = self.config.build_info
datasets = dict()
split = "train"
# create datasets
# [NOTE] return inner_datasets (wds.DataPipeline)
dataset_cls = self.train_dataset_cls
datasets[split] = dataset_cls(
vis_processor=self.vis_processors[split],
text_processor=self.text_processors[split],
location=build_info.storage,
).inner_dataset
return datasets
@registry.register_builder("cc_sbu_align")
class CCSBUAlignBuilder(BaseDatasetBuilder):
train_dataset_cls = CCSBUAlignDataset
DATASET_CONFIG_DICT = {
"default": "configs/datasets/cc_sbu/align.yaml",
}
def build_datasets(self):
# at this point, all the annotations and image/videos should be all downloaded to the specified locations.
logging.info("Building datasets...")
self.build_processors()
build_info = self.config.build_info
storage_path = build_info.storage
datasets = dict()
if not os.path.exists(storage_path):
warnings.warn("storage path {} does not exist.".format(storage_path))
# create datasets
dataset_cls = self.train_dataset_cls
datasets['train'] = dataset_cls(
vis_processor=self.vis_processors["train"],
text_processor=self.text_processors["train"],
ann_paths=[os.path.join(storage_path, 'filter_cap.json')],
vis_root=os.path.join(storage_path, 'image'),
)
return datasets
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