Dataset Versions
Versions
2022-08-26 11:57am
v30
· 2 years ago
2022-08-25 5:51pm
v29
· 2 years ago
2022-08-25 9:43am
v28
· 2 years ago
2022-08-21 3:58pm
v27
· 2 years ago
2022-08-10 7:54pm
v26
· 2 years ago
invoice_num_only
v25
· 3 years ago
mosaic_invoice_num
v24
· 3 years ago
normal_seller_buyer
v23
· 3 years ago
mosaic_seller_buyer
v22
· 3 years ago
mosaic_value
v21
· 3 years ago
mosaic
v20
· 3 years ago
gray_1
v19
· 3 years ago
new_templates_preproc_v1
v18
· 3 years ago
new_templates_v1
v17
· 3 years ago
big_v2
v16
· 3 years ago
big_v1
v15
· 3 years ago
2022-03-12 9:37pm
v14
· 3 years ago
reannotated
v13
· 3 years ago
semi-relabeled
v12
· 3 years ago
stretched
v11
· 3 years ago
2022-03-12 1:52pm
v10
· 3 years ago
2022-03-12 12:50pm
v9
· 3 years ago
full_no_preproc
v8
· 3 years ago
gray_big
v7
· 3 years ago
grayscale
v6
· 3 years ago
2022-02-06 7:59pm
v5
· 3 years ago
All_annotated_nr_date
v4
· 3 years ago
2022-01-31 8:51am
v3
· 3 years ago
2022-01-09 9:46pm
v2
· 3 years ago
Var1
v1
· 3 years ago
v18
new_templates_preproc_v1
Generated on Mar 14, 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.
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21232 Total Images
View All Images
Dataset Split
Train Set 92%
19632Images
Valid Set 8%
1600Images
Test Set %
0Images
Preprocessing
Auto-Orient: Applied
Resize: Fit (black edges) in 832x832
Auto-Adjust Contrast: Using Adaptive Equalization
Tile: 4 rows x 4 columns
Filter Null: Do not filter any null images.
Augmentations
Outputs per training example: 3
Rotation: Between -7° and +7°
Shear: ±7° Horizontal, ±7° Vertical
Grayscale: Apply to 25% of images
Noise: Up to 6% of pixels
Mosaic: Applied
Bounding Box: Rotation: Between -9° and +9°