Dataset Versions
Versions
2023-01-22 5:15pm
v27
· 2 years ago
2023-01-22 5:13pm
v26
· 2 years ago
polosan 2
v25
· 2 years ago
polosan 1
v23
· 2 years ago
2022-12-04 3-53pm
v22
· 2 years ago
bright ex cut
v21
· 2 years ago
3k noise bright
v20
· 2 years ago
3k blur cutout
v19
· 2 years ago
2022-11-27 6:35pm
v18
· 2 years ago
2022-11-23 2:31pm
v15
· 2 years ago
v14 salah
v14
· 2 years ago
2022-11-21 9:17pm
v13
· 2 years ago
2022-11-21 7:04pm
v12
· 2 years ago
2022-11-15 3:16pm
v11
· 2 years ago
2022-11-09 8:32pm
v10
· 2 years ago
2022-11-07 8:38pm
v9
· 2 years ago
2022-11-03 9:26pm
v8
· 2 years ago
2022-11-03 9:20pm
v7
· 2 years ago
2022-10-23 11:28pm
v6
· 2 years ago
2022-10-23 11:20pm
v5
· 2 years ago
2022-10-23 5:59pm
v4
· 2 years ago
2022-10-22 12:20am
v3
· 2 years ago
2022-10-20 9:21pm
v2
· 2 years ago
2022-10-20 12:43pm
v1
· 2 years ago
v26
2023-01-22 5:13pm
Generated on Jan 22, 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.
2694 Total Images
View All ImagesDataset Split
Train Set 87%
2355Images
Valid Set 8%
219Images
Test Set 4%
120Images
Preprocessing
Auto-Orient: Applied
Static Crop: 10-90% Horizontal Region, 10-90% Vertical Region
Resize: Stretch to 640x640
Augmentations
Outputs per training example: 3
Brightness: Between -15% and +15%
Exposure: Between -10% and +10%
Cutout: 25 boxes with 3% size each