Dataset Versions
Versions
2024-07-15 2:25pm
v41
· 5 months ago
2024-07-15 11:43am
v40
· 5 months ago
2024-07-15 11:10am
v39
· 5 months ago
2024-07-15 11:10am
v38
· 5 months ago
2024-07-14 2:52pm
v37
· 5 months ago
2024-07-13 9:03am
v36
· 5 months ago
2024-07-13 9:02am
v34
· 5 months ago
2024-07-11 5:41am
v33
· 5 months ago
2024-07-10 1:45pm
v32
· 5 months ago
2024-07-10 11:59am
v26
· 5 months ago
2024-07-10 10:20am
v21
· 5 months ago
2024-07-10 8:46am
v20
· 5 months ago
front cam version
v13
· 5 months ago
2024-07-05 7:07am
v12
· 5 months ago
2024-07-03 8:07am
v11
· 5 months ago
2024-07-03 7:11am
v10
· 5 months ago
2024-07-03 7:07am
v9
· 5 months ago
2024-07-03 6:38am
v8
· 5 months ago
2024-06-01 2:24pm
v7
· 6 months ago
2024-05-23 9:22pm
v6
· 7 months ago
2024-05-23 6:38pm
v5
· 7 months ago
2024-05-22 9:29pm
v4
· 7 months ago
2024-05-20 1:08pm
v3
· 7 months ago
2024-05-20 12:53pm
v2
· 7 months ago
2024-05-20 1:28am
v1
· 7 months ago
v13
front cam version
Generated on Jul 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.
899 Total Images
View All Images
Dataset Split
Train Set 90%
810Images
Valid Set 10%
89Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Augmentations
Outputs per training example: 2
Rotation: Between -15° and +15°
Blur: Up to 4.3px