Dataset Versions
Versions
2023-12-10 11:24pm
v27
· a year ago
2023-12-10 10:03pm
v26
· a year ago
2023-12-10 6:05pm
v25
· a year ago
2023-12-10 5:31pm
v24
· a year ago
2023-12-10 12:45pm
v23
· a year ago
2023-12-08 12:59pm
v20
· a year ago
2023-12-08 10:43am
v18
· a year ago
2023-12-08 10:42am
v17
· a year ago
2023-12-08 10:41am
v16
· a year ago
2023-12-08 10:39am
v15
· a year ago
2023-12-08 9:17am
v14
· a year ago
2023-12-07 10:45pm
v13
· a year ago
2023-12-07 10:42pm
v12
· a year ago
2023-12-07 10:40pm
v11
· a year ago
2023-12-07 6:51pm
v10
· a year ago
2023-12-02 10:37pm
v9
· a year ago
2023-12-02 10:22pm
v7
· a year ago
2023-12-02 9:56pm
v6
· a year ago
2023-12-02 9:52pm
v5
· a year ago
2023-12-02 9:21pm
v4
· a year ago
2023-12-02 3:44pm
v3
· a year ago
2023-12-02 10:58am
v2
· a year ago
2023-11-22 8:04pm
v1
· a year ago
v2
2023-12-02 10:58am
Generated on Dec 2, 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.
755 Total Images
View All Images
Dataset Split
Train Set 89%
669Images
Valid Set 7%
56Images
Test Set 4%
30Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 460x460
Auto-Adjust Contrast: Using Adaptive Equalization
Grayscale: Applied
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise
Rotation: Between -17° and +17°
Brightness: Between -35% and +35%
Noise: Up to 10% of pixels
Bounding Box: Flip: Horizontal
Bounding Box: Rotation: Between -15° and +15°
Bounding Box: Blur: Up to 2.5px
Bounding Box: Noise: Up to 7% of pixels