Dataset Versions
Versions
2023-12-16 9:13pm
v28
· a year ago
2023-11-13 7:12pm
v27
· a year ago
2023-11-13 6:58pm
v26
· a year ago
2023-11-13 6:27pm
v25
· a year ago
2023-08-25 6:52am
v24
· a year ago
2023-08-25 6:16am
v23
· a year ago
2023-08-25 5:46am
v22
· a year ago
2023-08-20 8:09am
v21
· a year ago
2023-08-20 6:56am
v20
· a year ago
2023-08-20 6:23am
v19
· a year ago
2023-08-19 11:05pm
v18
· a year ago
2023-08-19 6:37pm
v17
· a year ago
2023-08-19 6:25pm
v16
· a year ago
2023-08-19 6:04pm
v15
· a year ago
2023-08-19 5:13pm
v14
· a year ago
2023-08-19 7:48am
v13
· a year ago
2023-08-19 7:48am
v12
· a year ago
2023-08-19 6:58am
v11
· a year ago
2023-08-18 11:30pm
v10
· a year ago
2023-08-17 5:53pm
v9
· a year ago
2023-08-17 5:42pm
v8
· a year ago
2023-08-17 3:08pm
v7
· a year ago
2023-08-17 1:45pm
v6
· a year ago
2023-08-17 12:24pm
v5
· a year ago
2023-08-16 11:52pm
v4
· a year ago
2023-08-16 11:41pm
v3
· a year ago
2023-08-16 9:17pm
v2
· a year ago
2023-08-16 2:59pm
v1
· a year ago
v3
2023-08-16 11:41pm
Generated on Aug 16, 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.
179 Total Images
View All Images
Dataset Split
Train Set 87%
156Images
Valid Set 9%
16Images
Test Set 4%
7Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Brightness: Between -25% and +25%
Noise: Up to 5% of pixels
Cutout: 4 boxes with 10% size each
Bounding Box: Crop: 0% Minimum Zoom, 20% Maximum Zoom