Dataset Versions
Versions
2023-08-03 1:32pm
v32
· a year ago
2023-08-02 9:55am
v31
· a year ago
2023-08-01 12:44pm
v30
· a year ago
2023-07-27 5:27pm
v29
· a year ago
2023-07-27 1:01pm
v28
· a year ago
2023-07-27 11:30am
v27
· a year ago
2023-07-27 9:52am
v26
· a year ago
2023-07-26 12:16pm
v25
· a year ago
2023-07-26 11:29am
v24
· a year ago
2023-07-26 11:29am
v23
· a year ago
2023-07-26 11:29am
v22
· a year ago
2023-07-26 11:29am
v21
· a year ago
2023-07-26 11:26am
v20
· a year ago
2023-07-26 11:23am
v19
· a year ago
2023-07-24 9:01pm
v18
· a year ago
2023-07-24 5:29pm
v17
· a year ago
2023-07-24 5:26pm
v16
· a year ago
2023-07-24 9:36am
v15
· a year ago
2023-07-22 10:26pm
v14
· a year ago
2023-07-20 10:16am
v13
· a year ago
2023-07-20 10:14am
v12
· a year ago
2023-07-19 3:07pm
v11
· a year ago
2023-07-11 12:00pm
v10
· a year ago
2023-07-11 10:30am
v9
· a year ago
2023-07-11 10:19am
v8
· a year ago
2023-07-05 9:41am
v7
· a year ago
2023-07-04 1:35pm
v6
· a year ago
2023-06-30 1:34am
v5
· 2 years ago
2023-06-20 11:22pm
v4
· 2 years ago
2023-06-15 12:43am
v3
· 2 years ago
2023-06-14 5:41pm
v2
· 2 years ago
2023-06-11 6:03pm
v1
· 2 years ago
v19
2023-07-26 11:23am
Generated on Jul 26, 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.
2035 Total Images
View All Images
Dataset Split
Train Set 97%
1981Images
Valid Set 1%
25Images
Test Set 1%
29Images
Preprocessing
Isolate Objects: Applied
Static Crop: 25-75% Horizontal Region, 25-75% Vertical Region
Auto-Adjust Contrast: Using Adaptive Equalization
Filter Null: Require all images to contain annotations.
Augmentations
Outputs per training example: 3
Crop: 0% Minimum Zoom, 20% Maximum Zoom
Rotation: Between -15° and +15°
Grayscale: Apply to 12% of images
Hue: Between -4° and +4°
Saturation: Between -13% and +13%
Brightness: Between -25% and +25%
Exposure: Between -5% and +5%
Noise: Up to 1% of pixels
Mosaic: Applied
Bounding Box: Crop: 0% Minimum Zoom, 99% Maximum Zoom
Bounding Box: Shear: ±15° Horizontal, ±15° Vertical
Bounding Box: Brightness: Between -17% and +17%
Bounding Box: Noise: Up to 5% of pixels