Dataset Versions
Versions
2024-07-19 2:31am
v43
· 4 months ago
2024-07-09 8:03pm
v42
· 5 months ago
2024-06-16 12:57pm
v41
· 5 months ago
2024-06-15 4:54am
v40
· 5 months ago
2024-06-14 2:21am
v39
· 5 months ago
2024-06-11 4:41pm
v38
· 5 months ago
2024-06-10 12:23pm
v37
· 5 months ago
2024-06-10 6:26am
v36
· 5 months ago
2024-06-05 7:55am
v35
· 6 months ago
2024-06-03 7:42pm
v34
· 6 months ago
2024-06-03 5:34am
v33
· 6 months ago
2024-06-02 4:03pm
v32
· 6 months ago
2024-06-02 8:09am
v31
· 6 months ago
2024-06-01 10:33pm
v30
· 6 months ago
2024-06-01 7:15am
v26
· 6 months ago
2024-05-31 9:08am
v25
· 6 months ago
2024-05-27 11:19am
v22
· 6 months ago
2024-05-02 5:49am
v14
· 7 months ago
2024-05-01 5:47am
v13
· 7 months ago
2024-04-30 11:21am
v11
· 7 months ago
2024-04-28 3:51pm
v4
· 7 months ago
2024-03-24 6:02pm
v3
· 8 months ago
v38
2024-06-11 4:41pm
Generated on Jun 11, 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.
2672 Total Images
View All Images
Dataset Split
Train Set 84%
2256Images
Valid Set 10%
276Images
Test Set 5%
140Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 2 rows x 2 columns
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Brightness: Between -20% and +20%
Exposure: Between -2% and +2%
Blur: Up to 0.4px