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import logging
import os
import warnings
from bubogpt.common.registry import registry
from bubogpt.datasets.builders.multimodal_base_dataset_builder import MultimodalBaseDatasetBuilder
from bubogpt.datasets.datasets.audio_image.audio_image_datasets import AudioLocalizationDataset, AudioImageNegDataset
@registry.register_builder("vggss_align")
class VGGSSBuilderAudioImage(MultimodalBaseDatasetBuilder):
train_dataset_cls = AudioLocalizationDataset
DATASET_CONFIG_DICT = {
"default": "configs/datasets/vggss/align.yaml",
"3k": "configs/datasets/vggss/align3k.yaml",
"5k": "configs/datasets/vggss/align5k.yaml",
"31k": "configs/datasets/vggss/align31k.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))
print("Building datasets with: ", self.get_ann_files())
# create datasets
dataset_cls = self.train_dataset_cls
datasets['train'] = dataset_cls(
processors={**{
modal: self.processors[modal]["train"] for modal in self.data_type
}, **{
"text": self.processors["text"]["train"]
}},
roots={
modal: os.path.join(storage_path, f"{modal}s") for modal in self.data_type
},
# ann_paths=[os.path.join(storage_path, 'vggsound_balanced.json')],
ann_paths=self.get_ann_files(),
)
return datasets
def get_ann_files(self):
ann_files = self.config.build_info.get("ann_files", ["vggsound_balanced.json"])
return [os.path.join(self.config.build_info.storage, fname) for fname in ann_files]
@registry.register_builder("aud_img_neg")
class NegBuilderAudioImage(MultimodalBaseDatasetBuilder):
train_dataset_cls = AudioImageNegDataset
DATASET_CONFIG_DICT = {
"default": "configs/datasets/aud_img_neg/default.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
storage_path = {
"image": build_info.image.storage,
"audio": build_info.audio.storage,
}
ann_files = {
"image": build_info.image.ann_files,
"audio": build_info.audio.ann_files,
}
ann_paths = {
modal: [os.path.join(storage_path[modal], fname) for fname in ann_files[modal]] for modal in self.data_type
}
datasets = dict()
for path in storage_path.values():
if not os.path.exists(path):
warnings.warn("storage path {} does not exist.".format(path))
print("Building datasets with: ", ann_paths)
# create datasets
dataset_cls = self.train_dataset_cls
datasets['train'] = dataset_cls(
processors={**{
modal: self.processors[modal]["train"] for modal in self.data_type
}, **{
"text": self.processors["text"]["train"]
}},
roots={
modal: os.path.join(storage_path[modal], f"{modal}") for modal in self.data_type
},
ann_paths=ann_paths,
)
return datasets
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