Dataset Versions
Versions
2025-01-03 11:28am
v29
· 8 days ago
2025-01-02 10:53am
v28
· 9 days ago
2025-01-02 10:53am
v27
· 9 days ago
2025-01-02 10:52am
v26
· 9 days ago
2025-01-02 10:51am
v25
· 9 days ago
2025-01-02 10:50am
v24
· 9 days ago
2025-01-02 10:50am
v23
· 9 days ago
2025-01-02 10:49am
v22
· 9 days ago
2025-01-02 12:03am
v21
· 9 days ago
2024-12-29 2:56pm
v20
· 13 days ago
2024-12-29 2:53pm
v19
· 13 days ago
2024-12-29 10:47am
v18
· 13 days ago
2024-12-29 10:45am
v17
· 13 days ago
2024-12-28 1:45pm
v16
· 14 days ago
2024-12-27 6:00pm
v15
· 14 days ago
2024-12-24 10:12am
v14
· 18 days ago
2024-12-24 9:26am
v13
· 18 days ago
2024-12-23 11:27am
v12
· 19 days ago
2024-12-23 12:32am
v11
· 19 days ago
2024-12-23 12:27am
v10
· 19 days ago
2024-12-23 12:25am
v9
· 19 days ago
2024-12-19 8:39pm
v8
· 22 days ago
2024-12-19 4:27pm
v7
· 22 days ago
2024-12-19 4:21pm
v6
· 22 days ago
2024-12-19 4:16pm
v5
· 22 days ago
2024-12-19 2:15pm
v4
· 23 days ago
2024-12-19 2:14pm
v3
· 23 days ago
2024-12-12 7:37pm
v2
· a month ago
2024-12-12 12:07am
v1
· a month ago
v12
2024-12-23 11:27am
Generated on Dec 23, 2024
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.
686 Total Images
View All Images
Dataset Split
Train Set 81%
558Images
Valid Set 9%
64Images
Test Set 9%
64Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x480
Augmentations
Outputs per training example: 3
90° Rotate: Upside Down
Hue: Between -39° and +39°
Saturation: Between -47% and +47%
Brightness: Between -37% and +37%
Exposure: Between -23% and +23%
Blur: Up to 4.9px
Noise: Up to 1.73% of pixels
Cutout: 4 boxes with 19% size each