Dataset Versions
Versions
2023-06-02 1:18pm
v30
· 2 years ago
2023-06-02 1:12pm
v29
· 2 years ago
2023-06-01 8:36pm
v28
· 2 years ago
2023-05-28 5:30pm
v26
· 2 years ago
2023-05-26 2:33pm
v25
· 2 years ago
2023-04-26 1:02pm
v23
· 2 years ago
2023-04-25 10:33am
v22
· 2 years ago
2023-04-14 9:37pm
v21
· 2 years ago
2023-04-12 4:51pm
v20
· 2 years ago
2023-04-10 8:23pm
v19
· 2 years ago
2023-04-10 4:24pm
v18
· 2 years ago
2023-04-07 7:24pm
v16
· 2 years ago
2023-03-27 11:36am
v15
· 2 years ago
2023-03-20 9:07am
v14
· 2 years ago
2023-03-12 3:22pm
v13
· 2 years ago
2023-02-27 11:40am
v12
· 2 years ago
2023-02-27 11:36am
v11
· 2 years ago
2023-02-26 6:48pm
v10
· 2 years ago
2023-02-26 3:56pm
v9
· 2 years ago
2023-02-23 8:24pm
v4
· 2 years ago
2023-02-23 8:06pm
v3
· 2 years ago
test
v2
· 2 years ago
2023-02-22 11:30am
v1
· 2 years ago
v15
2023-03-27 11:36am
Generated on Mar 27, 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.
990 Total Images
View All Images
Dataset Split
Train Set 88%
867Images
Valid Set 7%
72Images
Test Set 5%
51Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 840x840
Modify Classes: 12 remapped, 0 dropped
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Grayscale: Apply to 25% of images
Saturation: Between -72% and +72%
Brightness: Between -50% and +0%