Dataset Versions
Versions
2025-01-01 12:21pm
v26
· 10 days ago
2024-12-11 8:11pm
v25
· a month ago
2024-12-11 7:07pm
v24
· a month ago
2024-12-10 7:31pm
v23
· a month ago
2024-12-10 1:49pm
v22
· a month ago
2024-12-06 7:06pm
v21
· a month ago
2024-12-06 5:25pm
v20
· a month ago
2024-12-06 1:46pm
v19
· a month ago
2024-12-06 11:08am
v18
· a month ago
2024-12-06 11:07am
v17
· a month ago
2024-12-06 11:07am
v16
· a month ago
2024-12-06 10:35am
v15
· a month ago
2024-12-04 10:40am
v14
· a month ago
2024-12-01 7:08pm
v13
· a month ago
2024-12-01 6:51pm
v12
· a month ago
2024-12-01 6:49pm
v11
· a month ago
2024-11-30 1:53pm
v10
· a month ago
2024-11-30 1:08pm
v9
· a month ago
2024-11-30 1:07pm
v8
· a month ago
2024-11-30 1:06pm
v7
· a month ago
2024-11-29 2:23pm
v6
· a month ago
2024-11-29 2:22pm
v5
· a month ago
2024-11-29 2:21pm
v4
· a month ago
2024-11-29 2:20pm
v3
· a month ago
2024-11-29 2:18pm
v2
· a month ago
2024-11-29 2:18pm
v1
· a month ago
v23
2024-12-10 7:31pm
Generated on Dec 10, 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.
3069 Total Images
View All Images
Dataset Split
Train Set 74%
2280Images
Valid Set 12%
361Images
Test Set 14%
428Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Rotation: Between -15° and +15°
Saturation: Between -34% and +34%
Brightness: Between -23% and +23%
Blur: Up to 0.8px
Noise: Up to 0.02% of pixels
