Dataset Versions
Versions
2024-08-09 7:45am
v35
· 3 months ago
2024-08-09 7:44am
v34
· 3 months ago
2024-07-25 8:06am
v33
· 3 months ago
2024-07-24 3:20pm
v32
· 3 months ago
2024-07-24 2:58pm
v31
· 3 months ago
2024-07-19 9:41am
v30
· 4 months ago
2024-07-18 3:41pm
v29
· 4 months ago
2024-07-18 3:40pm
v26
· 4 months ago
2024-07-18 9:44am
v24
· 4 months ago
2024-07-17 7:29am
v23
· 4 months ago
2024-07-16 4:11pm
v22
· 4 months ago
2024-07-16 3:35pm
v21
· 4 months ago
2024-07-11 2:34pm
v20
· 4 months ago
2024-07-11 1:17pm
v19
· 4 months ago
2024-07-10 12:16pm
v18
· 4 months ago
2024-07-10 10:23am
v17
· 4 months ago
2024-06-21 1:48pm
v16
· 5 months ago
2024-06-21 1:36pm
v15
· 5 months ago
2024-06-21 1:07pm
v14
· 5 months ago
2024-06-21 10:38am
v13
· 5 months ago
2024-06-21 10:19am
v12
· 5 months ago
2024-06-17 3:20pm
v11
· 5 months ago
2024-06-17 3:00pm
v10
· 5 months ago
2024-06-17 1:53pm
v6
· 5 months ago
2024-06-17 1:27pm
v5
· 5 months ago
2024-06-17 12:50pm
v4
· 5 months ago
2024-06-17 12:06pm
v3
· 5 months ago
2024-06-17 11:02am
v2
· 5 months ago
v20
2024-07-11 2:34pm
Generated on Jul 11, 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.
77 Total Images
View All Images
Dataset Split
Train Set 90%
69Images
Valid Set 9%
7Images
Test Set 1%
1Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (black edges) in 2048x2048
Augmentations
Outputs per training example: 3
Flip: Horizontal
Rotation: Between -8° and +8°
Hue: Between -15° and +15°
Saturation: Between -25% and +25%
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Blur: Up to 0.9px