We use the filtered synthetic captions prepared by BLIP. For more details about the dataset, please refer to BLIP.
It requires ~2.3T to store LAION and CC3M+CC12M+SBU datasets
Image source | Filtered synthetic caption by ViT-L |
---|---|
CC3M+CC12M+SBU | Download |
LAION115M | Download |
This will download two json files
ccs_synthetic_filtered_large.json
laion_synthetic_filtered_large.json
export MINIGPT4_DATASET=/YOUR/PATH/FOR/LARGE/DATASET/
mkdir ${MINIGPT4_DATASET}/cc_sbu
mkdir ${MINIGPT4_DATASET}/laion
mv ccs_synthetic_filtered_large.json ${MINIGPT4_DATASET}/cc_sbu
mv laion_synthetic_filtered_large.json ${MINIGPT4_DATASET}/laion
cp convert_cc_sbu.py ${MINIGPT4_DATASET}/cc_sbu
cp download_cc_sbu.sh ${MINIGPT4_DATASET}/cc_sbu
cp convert_laion.py ${MINIGPT4_DATASET}/laion
cp download_laion.sh ${MINIGPT4_DATASET}/laion
cd ${MINIGPT4_DATASET}/cc_sbu
python convert_cc_sbu.py
cd ${MINIGPT4_DATASET}/laion
python convert_laion.py
cd ${MINIGPT4_DATASET}/cc_sbu
sh download_cc_sbu.sh
cd ${MINIGPT4_DATASET}/laion
sh download_laion.sh
The final dataset structure
.
├── ${MINIGPT4_DATASET}
│ ├── cc_sbu
│ ├── convert_cc_sbu.py
│ ├── download_cc_sbu.sh
│ ├── ccs_synthetic_filtered_large.json
│ ├── ccs_synthetic_filtered_large.tsv
│ └── cc_sbu_dataset
│ ├── 00000.tar
│ ├── 00000.parquet
│ ...
│ ├── laion
│ ├── convert_laion.py
│ ├── download_laion.sh
│ ├── laion_synthetic_filtered_large.json
│ ├── laion_synthetic_filtered_large.tsv
│ └── laion_dataset
│ ├── 00000.tar
│ ├── 00000.parquet
│ ...
...
Then, set up the LAION dataset loading path in here at Line 5 as ${MINIGPT4_DATASET}/laion/laion_dataset/{00000..10488}.tar
and the Conceptual Captoin and SBU datasets loading path in here at Line 5 as ${MINIGPT4_DATASET}/cc_sbu/cc_sbu_dataset/{00000..01255}.tar