Dataset Versions
Versions
2023-09-23 9:41pm
v23
· a year ago
2023-09-14 4:20pm
v22
· a year ago
2023-09-14 3:58pm
v21
· a year ago
2023-09-14 3:54pm
v20
· a year ago
2023-09-14 3:42pm
v19
· a year ago
2023-09-14 12:52pm
v18
· a year ago
2023-09-12 12:49pm
v17
· a year ago
2023-09-12 8:35am
v16
· a year ago
2023-09-12 8:34am
v15
· a year ago
2023-09-12 7:10am
v14
· a year ago
2023-09-12 5:55am
v13
· a year ago
2023-09-11 7:13pm
v12
· a year ago
2023-09-11 7:02pm
v11
· a year ago
2023-09-11 6:57pm
v10
· a year ago
2023-09-10 2:22pm
v9
· a year ago
2023-09-10 2:15pm
v8
· a year ago
2023-09-10 10:08am
v7
· a year ago
2023-09-10 7:46am
v6
· a year ago
2023-09-10 1:09am
v5
· a year ago
2023-09-10 1:04am
v4
· a year ago
2023-09-10 1:03am
v3
· a year ago
2023-09-09 9:18am
v2
· a year ago
2023-09-09 8:57am
v1
· a year ago
v1
2023-09-09 8:57am
Generated on Sep 9, 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.
1759 Total Images
View All Images
Dataset Split
Train Set 94%
1650Images
Valid Set 3%
54Images
Test Set 3%
55Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 1280x1280
Tile: 2 rows x 2 columns
Filter Null: Require all images to contain annotations.
Augmentations
Outputs per training example: 3
Flip: Horizontal, Vertical
90° Rotate: Clockwise, Counter-Clockwise, Upside Down
Crop: 0% Minimum Zoom, 30% Maximum Zoom
Rotation: Between -15° and +15°
Shear: ±15° Horizontal, ±15° Vertical
Hue: Between -5° and +5°
Saturation: Between -25% and +25%
Brightness: Between -25% and +25%
Exposure: Between -25% and +25%
Blur: Up to 1.5px
Noise: Up to 1% of pixels
Mosaic: Applied
Bounding Box: Rotation: Between -25° and +25°
Bounding Box: Brightness: Between -25% and +25%