Dataset Versions
Versions
2024-01-15 10:11am
v29
· a year ago
2024-01-14 5:57pm
v28
· a year ago
2024-01-14 5:53pm
v27
· a year ago
2024-01-14 5:38pm
v26
· a year ago
2024-01-14 5:35pm
v25
· a year ago
2024-01-14 5:33pm
v24
· a year ago
2024-01-14 5:32pm
v23
· a year ago
2024-01-14 5:31pm
v22
· a year ago
2024-01-14 4:46pm
v21
· a year ago
2024-01-14 4:45pm
v20
· a year ago
2024-01-14 4:44pm
v19
· a year ago
2024-01-14 4:40pm
v18
· a year ago
2024-01-14 4:39pm
v17
· a year ago
2024-01-14 4:38pm
v16
· a year ago
2024-01-14 4:35pm
v15
· a year ago
2024-01-14 4:34pm
v14
· a year ago
2024-01-14 4:30pm
v13
· a year ago
2024-01-12 10:13am
v12
· a year ago
2024-01-12 9:32am
v11
· a year ago
2023-12-20 2:51pm
v10
· a year ago
2023-12-20 2:49pm
v9
· a year ago
2023-12-20 2:45pm
v8
· a year ago
2023-12-20 2:28pm
v7
· a year ago
2023-12-20 2:13pm
v6
· a year ago
2023-12-20 1:53pm
v5
· a year ago
2023-12-20 1:32pm
v4
· a year ago
2023-06-28 12:01pm
v3
· a year ago
2023-06-27 2:55pm
v2
· a year ago
2023-03-13 3:40pm
v1
· 2 years ago
v6
2023-12-20 2:13pm
Generated on Dec 20, 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.
2551 Total Images
View All Images
Dataset Split
Train Set 81%
2070Images
Valid Set 14%
360Images
Test Set 5%
121Images
Preprocessing
Auto-Orient: Applied
Isolate Objects: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -15° and +15°
Cutout: 3 boxes with 11% size each
Bounding Box: Flip: Horizontal