Dataset Versions
Versions
2024-10-29 10:35am
v31
· 23 days ago
2024-10-28 5:17pm
v30
· 24 days ago
2024-10-07 8:11am
v29
· a month ago
2024-10-03 12:21pm
v28
· 2 months ago
2024-05-03 10:36am
v27
· 7 months ago
2024-02-19 3:15pm
v26
· 9 months ago
2023-12-18 8:09am
v25
· a year ago
2023-12-16 8:19am
v24
· a year ago
2023-12-15 8:41pm
v23
· a year ago
2023-12-11 11:19am
v22
· a year ago
2023-11-27 8:30am
v21
· a year ago
2023-11-27 8:29am
v20
· a year ago
2023-11-22 8:41am
v19
· a year ago
2023-11-15 3:55pm
v18
· a year ago
2023-11-15 2:33pm
v17
· a year ago
2023-11-14 4:54pm
v16
· a year ago
2023-11-13 6:22pm
v15
· a year ago
2023-11-09 8:29am
v14
· a year ago
2023-11-03 12:56pm
v13
· a year ago
Segmonto12
v12
· a year ago
2023-10-23 5:39pm
v11
· a year ago
2023-10-23 3:07pm
v10
· a year ago
2023-10-23 9:55am
v9
· a year ago
2023-10-23 9:21am
v8
· a year ago
2023-10-18 10:52am
v7
· a year ago
2023-10-18 8:43am
v6
· a year ago
2023-10-17 6:21pm
v5
· a year ago
2023-10-16 8:40am
v4
· a year ago
2023-10-13 11:23am
v3
· a year ago
2023-10-13 11:23am
v2
· a year ago
2023-10-12 10:55am
v1
· a year ago
v19
2023-11-22 8:41am
Generated on Nov 22, 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.
6666 Total Images
View All Images
Dataset Split
Train Set 94%
6294Images
Valid Set 4%
248Images
Test Set 2%
124Images
Preprocessing
Modify Classes: 4 remapped, 0 dropped
Augmentations
Outputs per training example: 3
Rotation: Between -3° and +3°
Shear: ±3° Horizontal, ±3° Vertical
Exposure: Between -30% and +30%
Blur: Up to 1.5px
Noise: Up to 2% of pixels