Dataset Versions
Versions
2024-05-14 10:30am
v28
· 6 months ago
2024-05-07 4:41pm
v27
· 6 months ago
2024-04-24 10:00am
v26
· 7 months ago
2024-04-24 8:17am
v25
· 7 months ago
2024-04-21 7:18pm
v24
· 7 months ago
2024-04-19 3:01pm
v23
· 7 months ago
2024-04-19 2:41pm
v22
· 7 months ago
2024-04-19 2:26pm
v21
· 7 months ago
2024-04-19 2:20pm
v20
· 7 months ago
2024-04-19 2:10pm
v19
· 7 months ago
2024-04-19 1:49pm
v18
· 7 months ago
2024-04-19 1:44pm
v17
· 7 months ago
2024-04-19 1:09pm
v16
· 7 months ago
2024-04-18 1:41pm
v15
· 7 months ago
2024-04-18 1:34pm
v14
· 7 months ago
2024-04-16 1:28pm
v13
· 7 months ago
2024-03-28 3:01pm
v12
· 8 months ago
2024-03-15 3:52pm
v11
· 8 months ago
2024-03-11 12:33pm
v10
· 8 months ago
2024-03-06 10:41am
v9
· 9 months ago
2024-03-06 10:18am
v8
· 9 months ago
2024-03-04 6:21pm
v7
· 9 months ago
2024-03-04 6:18pm
v6
· 9 months ago
2024-03-02 5:36pm
v5
· 9 months ago
2024-03-01 10:07pm
v4
· 9 months ago
2024-03-01 7:06pm
v3
· 9 months ago
2024-03-01 5:13pm
v2
· 9 months ago
2024-03-01 4:34pm
v1
· 9 months ago
v20
2024-04-19 2:20pm
Generated on Apr 19, 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.
114 Total Images
View All ImagesDataset Split
Train Set 87%
99Images
Valid Set 8%
9Images
Test Set 5%
6Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Noise: Up to 0.5% of pixels