Dataset Versions
Versions
2024-12-07 3:25pm
v29
· 15 days ago
2024-12-06 5:42pm
v28
· 16 days ago
2024-12-06 1:06pm
v27
· 16 days ago
2024-12-06 1:05pm
v26
· 16 days ago
2024-12-06 1:02pm
v25
· 16 days ago
2024-12-06 1:01pm
v24
· 16 days ago
2024-12-06 1:01pm
v23
· 16 days ago
2024-12-06 12:49pm
v22
· 16 days ago
2024-12-06 12:48pm
v21
· 16 days ago
2024-12-06 12:45pm
v20
· 16 days ago
2024-12-06 12:44pm
v19
· 16 days ago
2024-12-06 12:43pm
v18
· 16 days ago
2024-12-06 12:43pm
v17
· 16 days ago
2024-12-04 7:22pm
v16
· 18 days ago
2024-12-04 7:14pm
v15
· 18 days ago
2024-12-04 7:11pm
v14
· 18 days ago
2024-12-04 7:10pm
v13
· 18 days ago
2024-12-04 7:09pm
v12
· 18 days ago
2024-12-04 7:06pm
v11
· 18 days ago
2024-12-04 6:56pm
v10
· 18 days ago
2024-12-04 6:16pm
v9
· 18 days ago
2024-12-04 6:07pm
v8
· 18 days ago
2024-12-04 6:06pm
v7
· 18 days ago
2024-12-04 6:01pm
v6
· 18 days ago
2024-12-01 8:11am
v5
· 21 days ago
2024-12-01 8:10am
v4
· 21 days ago
2024-12-01 8:09am
v3
· 21 days ago
2024-12-01 8:08am
v2
· 21 days ago
2024-12-01 8:02am
v1
· 21 days ago
v28
2024-12-06 5:42pm
Generated on Dec 6, 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.
568 Total Images
View All Images
Dataset Split
Train Set 100%
568Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Static Crop: 12-88% Horizontal Region, 0-100% Vertical Region
Resize: Stretch to 1280x720
Augmentations
Outputs per training example: 3
Flip: Horizontal