Dataset Versions
Versions
2022-05-04 3:27am
v22
· 3 years ago
2022-05-04 3:24am
v21
· 3 years ago
2022-05-04 3:21am
v20
· 3 years ago
Grayscale: Apply to 100- of images
v19
· 3 years ago
Cutout: 5 boxes with 5- size each2022-05-04 3:01am
v18
· 3 years ago
Grayscale:3x 100- 2022-05-03 11:58pm
v17
· 3 years ago
Mosaci 3x 2022-04-20 11:34pm
v14
· 3 years ago
3-10 Cutout 3x 2022-04-20 11:33pm
v13
· 3 years ago
5 Noise 3x 2022-04-20 11:33pm
v12
· 3 years ago
10px Blur 3x 2022-04-20 11:32pm
v11
· 3 years ago
25 Exposure 3x 2022-04-20 11:32pm
v10
· 3 years ago
25 Brightness 3x 2022-04-20 11:31pm
v9
· 3 years ago
25 Saturation 3x 2022-04-20 11:31pm
v8
· 3 years ago
20 Hue 3x 2022-04-20 11:30pm
v7
· 3 years ago
25 Grayscale 3x 2022-04-20 11:24pm
v6
· 3 years ago
15 Shear 3x 2022-04-20 11:23pm
v5
· 3 years ago
20 Rotation 3x 2022-04-20 11:22pm
v4
· 3 years ago
Crop 3x 2022-04-20 11:21pm
v3
· 3 years ago
90 rotate 3x 2022-04-20 11:21pm
v2
· 3 years ago
flip 3x 2022-04-20 11:20pm
v1
· 3 years ago
v2
90 rotate 3x 2022-04-20 11:21pm
Generated on Apr 20, 2022
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.
61 Total Images
View All Images
Dataset Split
Train Set 100%
61Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
No preprocessing steps were applied.
Augmentations
Outputs per training example: 3
90° Rotate: Clockwise, Counter-Clockwise, Upside Down