Dataset Versions
Versions
2023-07-15 9:50pm
v25
· a year ago
v16 no test
v24
· a year ago
v13 no test
v23
· a year ago
no augmentations no test
v22
· a year ago
hue- saturation- exposure
v21
· a year ago
2023-07-01 11:00am
v20
· a year ago
rotation- blur- mosaic -no test-
v19
· a year ago
90 rotate- crop- bbox hflip -no test-
v18
· a year ago
v13 grayscale
v17
· a year ago
rotation- blur- mosaic
v16
· a year ago
no augmentations
v15
· a year ago
90 rotate- crop- bbox hflip -resize fit black edges-
v14
· a year ago
90 rotate- crop- bbox hflip
v13
· a year ago
90 rotate- crop
v12
· a year ago
2023-06-17 11:11pm
v11
· a year ago
2023-06-14 11:38pm
v10
· a year ago
2023-06-14 2:09pm
v9
· a year ago
2023-06-14 1:07pm
v8
· a year ago
2023-06-08 12:55pm
v7
· a year ago
2023-06-08 12:50pm
v6
· a year ago
2023-05-25 2:25pm
v5
· a year ago
2023-05-25 2:13pm
v4
· a year ago
2023-05-25 9:37am
v3
· a year ago
v17
v13 grayscale
Generated on Jun 29, 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.
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234 Total Images
View All Images
Dataset Split
Train Set 86%
201Images
Valid Set 7%
17Images
Test Set 7%
16Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Grayscale: Applied
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Bounding Box: Flip: Horizontal