Dataset Versions
Versions
2024-01-20 2:17pm
v30
· a year ago
2024-01-20 2:12pm
v29
· a year ago
2024-01-20 2:08pm
v28
· a year ago
2024-01-16 7:42pm
v27
· a year ago
2024-01-10 7:33pm
v26
· a year ago
2024-01-10 2:15pm
v25
· a year ago
2024-01-05 9:44pm
v24
· a year ago
2024-01-04 7:37pm
v23
· a year ago
2024-01-04 12:53pm
v22
· a year ago
2023-12-25 11:13pm
v21
· a year ago
2023-12-25 10:32pm
v20
· a year ago
2023-12-22 11:46pm
v19
· a year ago
2023-12-20 4:59pm
v18
· a year ago
2023-12-20 11:16am
v17
· a year ago
2023-12-19 10:24am
v16
· a year ago
2023-12-16 9:55am
v15
· a year ago
2023-12-16 8:59am
v14
· a year ago
2023-12-15 8:11pm
v12
· a year ago
2023-12-15 6:51pm
v11
· a year ago
2023-12-14 6:32pm
v10
· a year ago
2023-12-14 5:18pm
v9
· a year ago
2023-12-14 2:31pm
v8
· a year ago
2023-12-14 1:11pm
v7
· a year ago
2023-12-12 5:32pm
v6
· a year ago
2023-12-12 1:42pm
v5
· a year ago
2023-12-12 10:59am
v4
· a year ago
2023-12-12 9:03am
v3
· a year ago
2023-12-09 3:45pm
v2
· a year ago
2023-12-09 3:01pm
v1
· a year ago
v14
2023-12-16 8:59am
Generated on Dec 16, 2023
Popular Download Formats
YOLOv11
TXT annotations and YAML config used with YOLOv11.
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv5
TXT annotations and YAML config used with YOLOv5.
YOLOv7
TXT annotations and YAML config used with YOLOv7.
COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
YOLO Darknet
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.
PaliGemma
PaliGemma JSONL format used for fine-tuning PaliGemma, Google's open multimodal vision model.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
Other Formats
Choose another format.
438 Total Images
View All Images
Dataset Split
Train Set 54%
236Images
Valid Set 39%
173Images
Test Set 7%
29Images
Preprocessing
Auto-Orient: Applied
Augmentations
No augmentations were applied.