license-plate-japan Image Dataset
Versions
2023-07-13 3:48pm
v36
Jul 13, 2023
2023-07-13 3:43pm
v34
Jul 13, 2023
2023-07-13 3:42pm
v33
Jul 13, 2023
2023-07-13 3:40pm
v32
Jul 13, 2023
2023-07-13 3:38pm
v31
Jul 13, 2023
2023-07-12 10:03pm
v30
Jul 12, 2023
2023-07-12 9:38pm
v29
Jul 12, 2023
2023-07-12 9:36pm
v28
Jul 12, 2023
2023-07-12 9:33pm
v27
Jul 12, 2023
2023-07-12 9:31pm
v26
Jul 12, 2023
2023-07-12 9:28pm
v25
Jul 12, 2023
2023-07-12 9:26pm
v24
Jul 12, 2023
2023-07-12 9:23pm
v23
Jul 12, 2023
2023-07-12 9:21pm
v22
Jul 12, 2023
2023-07-12 8:12am
v21
Jul 12, 2023
2023-07-12 8:03am
v19
Jul 12, 2023
2023-07-12 7:56am
v18
Jul 12, 2023
2023-07-12 7:54am
v17
Jul 12, 2023
2023-07-12 7:50am
v16
Jul 12, 2023
2023-07-12 7:49am
v15
Jul 12, 2023
2023-07-12 7:48am
v14
Jul 12, 2023
2023-07-12 7:46am
v13
Jul 12, 2023
2023-07-12 7:44am
v12
Jul 12, 2023
2023-07-11 4:27pm
v11
Jul 11, 2023
2023-07-11 4:20pm
v10
Jul 11, 2023
2023-07-11 4:19pm
v9
Jul 11, 2023
2023-07-11 4:19pm
v8
Jul 11, 2023
2023-07-11 4:18pm
v7
Jul 11, 2023
2023-07-11 3:42pm
v6
Jul 11, 2023
2023-07-11 3:28pm
v5
Jul 11, 2023
v36
2023-07-13 3:48pm
Generated on Jul 13, 2023
Popular Download Formats
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.
282 Total Images
View All ImagesDataset Split
Train Set 100%
282Images
Valid Set %
0Images
Test Set %
0Images
Preprocessing
No preprocessing steps were applied.
Augmentations
Outputs per training example: 3
Rotation: Between -5° and +5°
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