Dataset Versions
Versions
2023-10-21 10:25am
v27
· a year ago
2023-10-10 12:05am
v26
· a year ago
2023-10-09 11:37pm
v25
· a year ago
2023-10-09 11:18pm
v24
· a year ago
2023-10-07 8:16pm
v23
· a year ago
2023-10-07 8:01pm
v22
· a year ago
2023-10-07 7:50pm
v21
· a year ago
2023-10-07 6:46pm
v20
· a year ago
2023-10-07 6:20pm
v19
· a year ago
2023-10-07 6:13pm
v18
· a year ago
2023-10-07 5:53pm
v17
· a year ago
2023-10-07 5:34pm
v16
· a year ago
2023-10-07 5:10pm
v15
· a year ago
2023-10-05 12:52pm
v14
· a year ago
2023-10-05 12:33pm
v13
· a year ago
2023-10-05 12:07pm
v12
· a year ago
2023-10-05 12:00pm
v11
· a year ago
2023-10-04 3:25pm
v10
· a year ago
2023-10-04 3:18pm
v9
· a year ago
2023-10-04 3:11pm
v8
· a year ago
2023-10-04 2:51pm
v7
· a year ago
2023-10-03 1:00am
v6
· a year ago
2023-10-03 12:43am
v5
· a year ago
2023-10-03 12:34am
v4
· a year ago
2023-10-01 11:50pm
v3
· a year ago
2023-10-01 11:32pm
v2
· a year ago
2023-10-01 11:21pm
v1
· a year ago
v3
2023-10-01 11:50pm
Generated on Oct 1, 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.
133 Total Images
View All Images
Dataset Split
Train Set 86%
114Images
Valid Set 9%
12Images
Test Set 5%
7Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Brightness: Between -25% and +25%