Dataset Versions
Versions
2024-01-20 6:50pm
v28
· 10 months ago
2024-01-04 3:16pm
v27
· 10 months ago
2024-01-04 3:14pm
v26
· 10 months ago
2024-01-02 9:28pm
v25
· 10 months ago
2024-01-02 8:34pm
v24
· 10 months ago
2024-01-02 7:00pm
v23
· 10 months ago
2023-12-26 7:11am
v22
· 10 months ago
2023-12-26 5:45am
v21
· 10 months ago
2023-12-25 9:41pm
v20
· 10 months ago
2023-12-25 9:27pm
v19
· 10 months ago
2023-12-25 4:40pm
v18
· 10 months ago
2023-12-25 3:04pm
v17
· 10 months ago
2023-12-25 10:26am
v16
· 10 months ago
2023-12-25 7:58am
v15
· 10 months ago
2023-12-21 3:30pm
v14
· a year ago
2023-12-18 7:23am
v13
· a year ago
2023-12-09 10:29pm
v12
· a year ago
2023-12-04 9:01am
v11
· a year ago
2023-12-04 7:50am
v10
· a year ago
2023-12-04 12:34am
v9
· a year ago
2023-12-04 12:31am
v8
· a year ago
2023-12-03 12:44am
v7
· a year ago
2023-12-03 12:32am
v6
· a year ago
2023-12-03 12:28am
v5
· a year ago
2023-11-25 2:31am
v4
· a year ago
2023-11-25 2:30am
v3
· a year ago
2023-11-24 9:28pm
v2
· a year ago
2023-11-22 8:17pm
v1
· a year ago
v5
2023-12-03 12:28am
Generated on Dec 2, 2023
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.
649 Total Images
View All Images
Dataset Split
Train Set 82%
534Images
Valid Set 18%
115Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 2
Flip: Horizontal, Vertical
Bounding Box: Flip: Horizontal, Vertical
Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise
Bounding Box: Crop: 0% Minimum Zoom, 15% Maximum Zoom