Dataset Versions
Versions
2024-08-21 7:14am
v23
· 3 months ago
2024-08-16 3:23am
v22
· 3 months ago
2024-08-09 4:46am
v21
· 3 months ago
2024-08-06 10:31am
v20
· 3 months ago
2024-08-06 9:31am
v19
· 3 months ago
2024-08-06 8:53am
v18
· 3 months ago
2024-08-01 7:59am
v17
· 3 months ago
2024-07-31 9:13am
v16
· 3 months ago
2024-07-31 6:24am
v15
· 3 months ago
2024-07-31 5:05am
v14
· 3 months ago
2024-07-31 3:50am
v13
· 3 months ago
2024-07-30 7:25am
v12
· 3 months ago
2024-07-30 4:54am
v11
· 3 months ago
2024-07-30 4:50am
v10
· 3 months ago
2024-07-25 7:01am
v9
· 4 months ago
2024-07-25 4:15am
v8
· 4 months ago
2024-07-25 4:11am
v7
· 4 months ago
2024-07-25 2:35am
v6
· 4 months ago
2024-07-24 10:22am
v5
· 4 months ago
2024-07-24 8:07am
v4
· 4 months ago
2024-07-24 5:07am
v3
· 4 months ago
2024-07-23 10:10am
v2
· 4 months ago
v23
2024-08-21 7:14am
Generated on Aug 21, 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.
1068 Total Images
View All Images
Dataset Split
Train Set 87%
933Images
Valid Set 10%
111Images
Test Set 2%
24Images
Preprocessing
Static Crop: 0-100% Horizontal Region, 0-100% Vertical Region
Resize: Fit within 640x640
Tile: 1 rows x 3 columns
Augmentations
Outputs per training example: 3
Rotation: Between -2° and +2°
Blur: Up to 0.2px