Dataset Versions
Versions
2023-10-26 4:08pm
v28
· a year ago
2023-10-08 1:02am
v27
· a year ago
2023-10-08 12:05am
v26
· a year ago
2023-10-06 6:38pm
v25
· a year ago
2023-10-06 6:37pm
v24
· a year ago
2023-10-06 4:00pm
v23
· a year ago
2023-10-06 3:28pm
v22
· a year ago
2023-10-06 2:28am
v21
· a year ago
2023-10-06 12:09am
v20
· a year ago
2023-10-06 12:02am
v19
· a year ago
2023-10-05 11:33pm
v18
· a year ago
2023-10-05 11:14pm
v17
· a year ago
2023-10-04 7:59pm
v16
· a year ago
2023-10-04 7:21pm
v15
· a year ago
2023-10-03 1:18am
v14
· a year ago
2023-09-18 6:16pm
v13
· a year ago
2023-09-15 3:11pm
v12
· a year ago
2023-09-14 10:35pm
v11
· a year ago
2023-09-14 10:04pm
v10
· a year ago
2023-09-14 9:46pm
v9
· a year ago
2023-09-14 6:01pm
v8
· a year ago
2023-09-14 2:55am
v7
· a year ago
2023-09-14 2:23am
v6
· a year ago
2023-09-14 1:55am
v5
· a year ago
2023-09-14 1:22am
v4
· a year ago
2023-09-13 11:32pm
v3
· a year ago
2023-09-13 9:53pm
v2
· a year ago
2023-09-13 9:06pm
v1
· a year ago
v19
2023-10-06 12:02am
Generated on Oct 5, 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.
1567 Total Images
View All Images
Dataset Split
Train Set 92%
1440Images
Valid Set 5%
71Images
Test Set 4%
56Images
Preprocessing
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Flip: Horizontal
Grayscale: Apply to 10% of images
Saturation: Between -54% and +54%
Brightness: Between -21% and +21%
Exposure: Between -6% and +6%
Blur: Up to 0.75px
Noise: Up to 2% of pixels