Dataset Versions
Versions
2023-05-24 10:17pm
v36
· a year ago
2023-05-24 10:11pm
v35
· a year ago
2023-05-24 10:06pm
v34
· a year ago
2023-05-24 9:08pm
v33
· a year ago
2023-05-24 9:02pm
v32
· a year ago
2023-05-24 9:00pm
v31
· a year ago
2023-05-24 8:51pm
v30
· a year ago
2023-05-24 8:47pm
v29
· a year ago
2023-05-24 7:37pm
v26
· a year ago
2023-05-24 7:33pm
v25
· a year ago
2023-05-24 7:32pm
v24
· a year ago
2023-05-24 7:29pm
v23
· a year ago
2023-05-24 7:28pm
v22
· a year ago
2023-05-24 7:25pm
v21
· a year ago
2023-05-24 7:21pm
v20
· a year ago
2023-05-24 7:19pm
v19
· a year ago
2023-05-24 7:17pm
v18
· a year ago
2023-05-24 7:15pm
v17
· a year ago
2023-05-24 7:14pm
v16
· a year ago
2023-05-24 6:46pm
v15
· a year ago
2023-05-24 4:45pm
v14
· a year ago
2023-05-24 4:33pm
v12
· a year ago
2023-05-24 4:25pm
v10
· a year ago
2023-05-24 4:25pm
v9
· a year ago
2023-05-24 4:21pm
v8
· a year ago
2023-05-24 4:19pm
v7
· a year ago
2023-05-24 4:16pm
v6
· a year ago
2023-05-24 4:14pm
v5
· a year ago
2023-05-24 4:13pm
v4
· a year ago
2023-05-24 4:11pm
v3
· a year ago
2023-05-24 4:09pm
v2
· a year ago
2023-05-24 4:07pm
v1
· a year ago
v36
2023-05-24 10:17pm
Generated on May 24, 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.
948 Total Images
View All Images
Dataset Split
Train Set 89%
843Images
Valid Set 7%
71Images
Test Set 4%
34Images
Preprocessing
Auto-Orient: Applied
Resize: Fit within 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
Shear: ±15° Horizontal, ±15° Vertical
Grayscale: Apply to 49% of images
Hue: Between -98° and +98°
Saturation: Between -53% and +53%
Exposure: Between -36% and +36%
Mosaic: Applied
Bounding Box: Brightness: Between -32% and +32%
Bounding Box: Exposure: Between -21% and +21%