Dataset Versions
Versions
2024-09-27 12:23am
v26
· a month ago
2024-09-26 11:44am
v25
· 2 months ago
2024-09-26 11:11am
v24
· 2 months ago
2024-09-26 10:24am
v23
· 2 months ago
2024-09-26 8:24am
v22
· 2 months ago
2024-09-26 8:03am
v21
· 2 months ago
2024-09-26 2:28am
v20
· 2 months ago
2024-09-26 12:14am
v19
· 2 months ago
2024-09-25 9:35pm
v18
· 2 months ago
2024-09-25 9:00pm
v17
· 2 months ago
2024-09-25 2:00pm
v16
· 2 months ago
2024-09-25 1:04pm
v15
· 2 months ago
2024-09-25 11:54am
v14
· 2 months ago
2024-09-25 10:53am
v13
· 2 months ago
2024-09-25 9:46am
v12
· 2 months ago
2024-09-25 8:28am
v11
· 2 months ago
2024-09-25 6:57am
v10
· 2 months ago
2024-09-24 2:55pm
v9
· 2 months ago
2024-09-24 12:22pm
v8
· 2 months ago
2024-09-23 12:21pm
v7
· 2 months ago
2024-09-23 12:24am
v6
· 2 months ago
2024-09-09 1:26am
v5
· 2 months ago
2024-09-05 9:43am
v4
· 2 months ago
2024-09-03 7-54am
v3
· 2 months ago
2024-09-02 12:10pm
v2
· 2 months ago
2024-09-02 7:29am
v1
· 2 months ago
v4
2024-09-05 9:43am
Generated on Sep 5, 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.
Other Formats
Choose another format.
1865 Total Images
View All Images
Dataset Split
Train Set 88%
1632Images
Valid Set 8%
155Images
Test Set 4%
78Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal
90° Rotate: Clockwise, Counter-Clockwise
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Grayscale: Apply to 15% of images
Blur: Up to 2.5px
Noise: Up to 0.1% of pixels
Cutout: 5 boxes with 10% size each