Dataset Versions
Versions
2023-09-01 6:08pm
v34
· a year ago
2023-09-01 5:34pm
v33
· a year ago
2022-11-22 10:20pm
v32
· 2 years ago
2022-11-15 5:36pm
v31
· 2 years ago
2022-11-08 3:10pm
v30
· 2 years ago
2022-10-07 10:51am
v29
· 2 years ago
2022-10-06 2:23pm
v28
· 2 years ago
2022-10-05 5:03pm
v27
· 2 years ago
2022-09-19 12:18am
v26
· 2 years ago
2022-09-18 2:33pm
v25
· 2 years ago
2022-09-17 10:48am
v24
· 2 years ago
2022-09-16 6:11pm
v23
· 2 years ago
2022-09-14 6:41pm
v22
· 2 years ago
2022-08-10 6:07pm
v21
· 2 years ago
2022-08-10 11:13am
v20
· 2 years ago
2022-08-10 10:40am
v19
· 2 years ago
2022-05-31 5:36pm
v18
· 2 years ago
Invoice 11
v17
· 2 years ago
Invoice 10
v16
· 2 years ago
Invoice 9
v15
· 2 years ago
Invoice 8
v14
· 2 years ago
Invoice 7
v13
· 2 years ago
Invoice 6
v12
· 2 years ago
Invoice 6
v11
· 2 years ago
Invoice 5
v10
· 2 years ago
Invoice 4
v9
· 2 years ago
Invoice 3
v3
· 2 years ago
Invoice 2022-05-13
v2
· 2 years ago
INVOICE01
v1
· 2 years ago
v24
2022-09-17 10:48am
Generated on Sep 17, 2022
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.
936 Total Images
View All ImagesDataset Split
Train Set 87%
818Images
Valid Set 8%
73Images
Test Set 5%
45Images
Preprocessing
Auto-Orient: Applied
Resize: Stretch to 860x860
Auto-Adjust Contrast: Using Adaptive Equalization
Modify Classes: 5 remapped, 6 dropped
Augmentations
Outputs per training example: 3
Brightness: Between -15% and +15%