Dataset Versions
Versions
2024-11-06 12:54am
v30
· 8 days ago
2aug-nonpre
v29
· 11 days ago
2aug-brightness_2pre
v28
· 14 days ago
2aug_2Prepro recom
v27
· 18 days ago
Auto-Orient-Isolate Objects-Resize
v26
· 18 days ago
combine-2aug-non_pre
v25
· 20 days ago
Preprocessing Auto-Orient- Resize
v24
· 20 days ago
Grayscale
v23
· 20 days ago
Isolate Objects
v22
· 20 days ago
Static Crop
v21
· 20 days ago
Resize
v20
· 20 days ago
2aug_Prepro Auto orient
v19
· 21 days ago
2aug_non preprocess
v18
· 21 days ago
shizu_Brightness30
v17
· 23 days ago
shizu_Brightness15
v16
· 24 days ago
Auto-Orient
v15
· 24 days ago
shizu_rotation30
v14
· 25 days ago
shizu_rotation15
v13
· a month ago
shizu_Crop30
v12
· a month ago
shizu_Crop20
v11
· a month ago
shizu_Gray30
v10
· a month ago
non-augmentation non-preprocessing
v9
· a month ago
shizu_Gray15
v8
· a month ago
shizu_Flip_hori-verti
v7
· a month ago
shizu_Flip_vertical
v6
· a month ago
shizu_Flip_horizontal
v5
· a month ago
2024-09-22 4:35am
v3
· 2 months ago
prepro_aug
v2
· 2 months ago
2024-09-21 8:33am
v1
· 2 months ago
v6
shizu_Flip_vertical
Generated on Oct 15, 2024
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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1382 Total Images
View All Images
Dataset Split
Train Set 81%
1113Images
Valid Set 13%
179Images
Test Set 7%
90Images
Preprocessing
No preprocessing steps were applied.
Augmentations
Outputs per training example: 3
Flip: Vertical