Dataset Versions
Versions
2024-02-05 3:22pm
v23
· 9 months ago
2024-02-05 2:43pm
v22
· 9 months ago
2024-02-05 12:57pm
v21
· 9 months ago
2024-02-05 11:47am
v20
· 9 months ago
2024-02-03 8:53pm
v19
· 9 months ago
2024-02-02 8:36am
v18
· 9 months ago
2024-02-01 10:24am
v17
· 9 months ago
2024-02-01 10:21am
v16
· 9 months ago
2024-01-31 12:15pm
v15
· 9 months ago
2024-01-31 12:04pm
v14
· 9 months ago
2024-01-30 5:53am
v13
· 10 months ago
2024-01-29 10:22pm
v12
· 10 months ago
2024-01-29 8:02am
v11
· 10 months ago
2024-01-28 9:35am
v10
· 10 months ago
2024-01-28 6:16am
v9
· 10 months ago
2024-01-27 5:23pm
v8
· 10 months ago
2024-01-27 10:15am
v7
· 10 months ago
2024-01-27 10:14am
v6
· 10 months ago
2024-01-26 9:51pm
v5
· 10 months ago
2024-01-26 9:43pm
v4
· 10 months ago
2024-01-26 9:42pm
v3
· 10 months ago
2024-01-26 9:41pm
v2
· 10 months ago
2024-01-27 4:24am
v1
· 10 months ago
v23
2024-02-05 3:22pm
Generated on Feb 5, 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.
12457 Total Images
View All Images
Dataset Split
Train Set 87%
10880Images
Valid Set 8%
1019Images
Test Set 4%
558Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 1280x720
Augmentations
Outputs per training example: 3
Grayscale: Apply to 20% of images
Brightness: Between -20% and +20%