Dataset Versions
Versions
2024-05-09 10:20pm
v26
· 6 months ago
2024-05-09 6:52pm
v25
· 6 months ago
2024-05-09 1:38pm
v24
· 6 months ago
2024-04-26 6:54pm
v23
· 6 months ago
2024-04-26 1:38pm
v22
· 6 months ago
MIxed Dataset-only rotation aug
v21
· 6 months ago
2024-04-09 2:42pm
v20
· 7 months ago
2024-04-09 2:08pm
v19
· 7 months ago
2024-04-08 1:20am
v18
· 7 months ago
2024-04-07 9:21pm
v17
· 7 months ago
2024-04-07 9:21pm
v16
· 7 months ago
2024-04-07 4:37pm
v15
· 7 months ago
2024-04-07 4:36pm
v14
· 7 months ago
2024-04-07 2:08pm
v13
· 7 months ago
2024-04-07 1:59pm
v12
· 7 months ago
NO Augment NO Auto orient
v11
· 7 months ago
2024-04-06 9:16pm
v10
· 7 months ago
2024-04-06 9:05pm
v9
· 7 months ago
2024-03-17 12:38am
v8
· 8 months ago
2024-03-17 12:36am
v7
· 8 months ago
2024-03-17 12:07am
v6
· 8 months ago
2024-02-26 1:12am
v5
· 8 months ago
2024-02-26 12:56am
v4
· 8 months ago
2024-02-26 12:39am
v3
· 8 months ago
2024-02-24 6:42pm
v2
· 8 months ago
2024-02-22 1:20am
v1
· 8 months ago
v15
2024-04-07 4:37pm
Generated on Apr 7, 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.
1664 Total Images
View All ImagesDataset Split
Train Set 89%
1481Images
Valid Set 5%
91Images
Test Set 6%
92Images
Preprocessing
Resize: Stretch to 640x640
Filter Null: Require at least 59% of images to contain annotations.
Augmentations
Outputs per training example: 3
Rotation: Between -15° and +15°