Dataset Versions
Versions
2023-08-26 2:56pm
v25
· a year ago
2023-08-26 2:33pm
v24
· a year ago
2023-08-26 2:27pm
v23
· a year ago
2023-08-26 2:27pm
v22
· a year ago
2023-08-25 1:48pm
v21
· a year ago
2023-08-24 1:37pm
v20
· a year ago
2023-08-24 1:28pm
v19
· a year ago
2023-08-24 11:05am
v18
· a year ago
2023-08-24 10:31am
v17
· a year ago
2023-08-23 2:59pm
v16
· a year ago
2023-08-23 2:58pm
v15
· a year ago
2023-08-23 9:45am
v14
· a year ago
2023-08-22 8:20pm
v13
· a year ago
2023-08-22 8:19pm
v12
· a year ago
2023-08-22 8:19pm
v11
· a year ago
2023-08-22 8:19pm
v10
· a year ago
2023-08-20 10:07pm
v9
· a year ago
2023-08-20 10:01pm
v8
· a year ago
2023-08-20 9:14pm
v7
· a year ago
2023-08-20 8:43pm
v6
· a year ago
2023-08-20 4:31pm
v5
· a year ago
2023-08-20 3:42pm
v4
· a year ago
2023-08-17 4:50pm
v3
· a year ago
2023-08-17 4:46pm
v2
· a year ago
2023-08-17 3:08pm
v1
· a year ago
v22
2023-08-26 2:27pm
Generated on Aug 26, 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.
228 Total Images
View All Images
Dataset Split
Train Set 82%
186Images
Valid Set 14%
32Images
Test Set 4%
10Images
Preprocessing
Auto-Orient: Applied
Resize: Fit within 320x320
Augmentations
Outputs per training example: 3
Flip: Horizontal
Crop: 0% Minimum Zoom, 10% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 25% of images
Noise: Up to 5% of pixels
Cutout: 3 boxes with 10% size each
Bounding Box: Brightness: Between -20% and +20%
Bounding Box: Blur: Up to 1.25px