Dataset Versions
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v61
· 2 years ago
17.10
v60
· 2 years ago
17.9
v59
· 2 years ago
17.8
v58
· 2 years ago
17.7
v57
· 2 years ago
17.6
v56
· 2 years ago
17.5
v55
· 2 years ago
17.4
v54
· 2 years ago
17.3
v53
· 2 years ago
17.2
v52
· 2 years ago
17.1
v51
· 2 years ago
16.640
v50
· 2 years ago
16.416
v49
· 2 years ago
16 -beta-
v48
· 2 years ago
15v1.896
v47
· 2 years ago
15v1.640
v46
· 2 years ago
15v1.448
v45
· 2 years ago
15v1
v44
· 2 years ago
15
v43
· 2 years ago
14.7-1-2
v42
· 2 years ago
14.7-2-1
v41
· 2 years ago
12.7-1-2
v37
· 2 years ago
12.7-2-1
v36
· 2 years ago
11.6-2-2
v35
· 2 years ago
11.7-1-2
v34
· 2 years ago
11.7-2-1
v32
· 2 years ago
6.2.640
v31
· 3 years ago
6.2.416
v30
· 3 years ago
6.3
v22
· 3 years ago
6.2
v21
· 3 years ago
6.1
v20
· 3 years ago
10.0
v19
· 3 years ago
9.0 OK
v18
· 3 years ago
8.0
v17
· 3 years ago
7.0 OK
v16
· 3 years ago
6.0 OK
v15
· 3 years ago
5.0 OK
v14
· 3 years ago
4.0 OK
v13
· 3 years ago
3.0 OK
v12
· 3 years ago
2.0
v11
· 3 years ago
1.0
v10
· 3 years ago
009 OK
v9
· 3 years ago
008
v8
· 3 years ago
007 OK
v7
· 3 years ago
006
v6
· 3 years ago
v5
v5
· 3 years ago
v3
v4
· 3 years ago
v2
v2
· 3 years ago
v1
v1
· 3 years ago
v46
15v1.640
Generated on Nov 21, 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.
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720 Total Images
View All Images
Dataset Split
Train Set 88%
630Images
Valid Set 4%
30Images
Test Set 8%
60Images
Preprocessing
Resize: Fit (black edges) in 640x640
Augmentations
Outputs per training example: 3
Crop: 0% Minimum Zoom, 10% Maximum Zoom
Rotation: Between -5° and +5°
Hue: Between -15° and +15°
Saturation: Between -15% and +15%
Brightness: Between -15% and +15%
Exposure: Between -15% and +15%
Blur: Up to 0.75px
Cutout: 4 boxes with 5% size each
Mosaic: Applied