Dataset Versions
Versions
2024-06-30 9:24am
v25
· 5 months ago
2024-06-30 8:55am
v24
· 5 months ago
2024-06-30 8:52am
v23
· 5 months ago
2024-06-30 7:43am
v22
· 5 months ago
2024-06-29 8:32pm
v21
· 5 months ago
2024-06-29 4:31pm
v20
· 5 months ago
2024-06-29 12:47pm
v19
· 5 months ago
2024-06-29 8:13am
v18
· 5 months ago
2024-06-29 8:05am
v17
· 5 months ago
2024-06-29 4:44am
v16
· 5 months ago
2024-06-29 1:34am
v15
· 5 months ago
2024-06-28 6:29pm
v14
· 5 months ago
2024-06-28 3:03pm
v13
· 5 months ago
2024-06-28 11:40am
v12
· 5 months ago
2024-06-28 6:46am
v11
· 5 months ago
2024-06-28 1:35am
v10
· 5 months ago
2024-06-27 5:25pm
v9
· 5 months ago
2024-06-27 11:48am
v8
· 5 months ago
2024-06-27 1:37am
v7
· 5 months ago
2024-06-22 2:43am
v6
· 5 months ago
2024-06-21 5:51pm
v5
· 5 months ago
2024-06-21 5:50pm
v4
· 5 months ago
2024-06-21 5:49pm
v3
· 5 months ago
2024-06-21 5:48pm
v2
· 5 months ago
2024-06-21 4:13pm
v1
· 5 months ago
v13
2024-06-28 3:03pm
Generated on Jun 28, 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.
1140 Total Images
View All Images
Dataset Split
Train Set 100%
1140Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Augmentations
Outputs per training example: 3
Flip: Horizontal
Rotation: Between -12° and +12°