Dataset Versions
Versions
2023-07-11 10:23am
v1478
· a year ago
2023-07-10 4:03pm
v1477
· a year ago
2023-07-10 3:53pm
v1476
· a year ago
2023-07-10 3:43pm
v1475
· a year ago
2023-07-10 3:39pm
v1474
· a year ago
2023-07-10 3:33pm
v1473
· a year ago
2023-07-10 3:23pm
v1484
· a year ago
2023-07-10 3:23pm
v1483
· a year ago
2023-07-10 3:23pm
v1482
· a year ago
2023-07-10 3:23pm
v1481
· a year ago
2023-07-10 3:22pm
v1480
· a year ago
2023-07-10 3:22pm
v1479
· a year ago
2023-07-10 3:22pm
v1472
· a year ago
2023-07-10 3:22pm
v1471
· a year ago
2023-07-10 3:22pm
v1470
· a year ago
2023-07-10 3:22pm
v1469
· a year ago
2023-07-10 3:20pm
v1495
· a year ago
2023-07-10 3:20pm
v1494
· a year ago
2023-07-10 3:20pm
v1493
· a year ago
2023-07-10 3:20pm
v1492
· a year ago
2023-07-10 3:20pm
v1491
· a year ago
2023-07-10 3:20pm
v1490
· a year ago
2023-07-10 3:20pm
v1489
· a year ago
2023-07-10 3:20pm
v1488
· a year ago
2023-07-10 3:20pm
v1487
· a year ago
2023-07-10 3:20pm
v1486
· a year ago
2023-07-10 3:19pm
v1485
· a year ago
v1495
2023-07-10 3:20pm
Generated on Jul 10, 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.
831 Total Images
View All Images
Dataset Split
Train Set 90%
744Images
Valid Set 5%
45Images
Test Set 5%
42Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Rotation: Between -11° and +11°
Shear: ±15° Horizontal, ±15° Vertical
Blur: Up to 3px
Noise: Up to 5% of pixels
Cutout: 3 boxes with 16% size each