- Osprey-724K 🤗 download
Data | Size |
---|---|
osprey_short_form.json | 57 MB |
osprey_conversation.json | 106 MB |
osprey_detail_description.json | 63.4 MB |
osprey_part_level.json | 153 MB |
osprey_lvis_positive_negative.json | 140 MB |
- COCO: train2017,
imgs
should contain all the images including training set and validation set. - pascal_part: train.json, VOCdevkit.
- partImagenet: train_format.json, PartImageNet_OOD.
- refcocos: refcoco, refcoco+.
- vg: vg_train_with_mask.json (mask is generated from HQ-SAM), images can be downloaded from OpendataLab,
image
should contain all the vg images(VG_100K and VG_100K_2). - vcr: vcr.
After downloading all of them, organize the data as follows in ./data
,
├── coco
│ ├── annotations
│ │ └── instances_train2017.json
│ └── imgs
├── part data
│ ├── pascal_part
│ │ ├── train.json
│ │ └── VOCdevkit
│ └── partImagenet
│ ├── train_format.json
│ └── train
├── refcocos
│ ├── finetune_refcoco_train_with_mask.json
│ └── finetune_refcoco+_train_with_mask.json
├── Osprey-724K
│ ├── osprey_short_form.json
│ ├── osprey_conversation.json
│ ├── osprey_detail_description.json
│ ├── osprey_part_level.json
│ └── osprey_lvis_positive_negative.json
├── vg
│ ├── vg_train_with_mask.json
│ └── image
└── vcr
├── train.jsonl
└── vcr1images