Dataset Versions
Versions
2023-08-21 12:47pm
v32
· a year ago
2023-08-20 1:25am
v31
· a year ago
2023-08-16 8:53pm
v30
· a year ago
2023-08-16 12:38pm
v29
· a year ago
2023-08-16 11:35am
v28
· a year ago
2023-08-16 10:07am
v27
· a year ago
2023-05-28 1:52pm
v26
· 2 years ago
2023-05-28 1:46pm
v25
· 2 years ago
2023-04-10 5:57am
v24
· 2 years ago
2023-04-05 10:43pm
v23
· 2 years ago
2023-04-05 10:34pm
v22
· 2 years ago
2023-04-05 10:25pm
v21
· 2 years ago
2023-04-03 1:17pm
v18
· 2 years ago
2023-03-21 7:30pm
v17
· 2 years ago
2023-03-13 12:03pm
v16
· 2 years ago
2023-03-13 1:44am
v15
· 2 years ago
2023-03-08 9:58am
v14
· 2 years ago
2023-03-06 3:49pm
v13
· 2 years ago
2023-03-04 11:36am
v12
· 2 years ago
2023-03-02 3:52pm
v11
· 2 years ago
2023-03-02 1:56pm
v10
· 2 years ago
2023-03-02 12:46am
v9
· 2 years ago
2023-03-01 11:28am
v8
· 2 years ago
2023-02-21 11:43pm
v7
· 2 years ago
2023-02-21 8:01pm
v6
· 2 years ago
2023-02-21 3:35pm
v5
· 2 years ago
2023-02-21 1:09pm
v4
· 2 years ago
2023-02-03 10:45pm
v3
· 2 years ago
2023-02-03 2:25am
v2
· 2 years ago
2023-02-03 2-23am
v1
· 2 years ago
v24
2023-04-10 5:57am
Generated on Apr 10, 2023
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.
983 Total Images
View All Images
Dataset Split
Train Set 92%
903Images
Valid Set 5%
50Images
Test Set 3%
30Images
Preprocessing
Resize: Fit within 640x640
Augmentations
Outputs per training example: 3
Crop: 20% Minimum Zoom, 49% Maximum Zoom
Shear: ±33° Horizontal, ±22° Vertical
Hue: Between -25° and +25°
Saturation: Between -50% and +50%
Blur: Up to 5px
Bounding Box: Exposure: Between -22% and +22%
Bounding Box: Blur: Up to 4.5px