Dataset Versions
Versions
2024-07-10 4:46pm
v43
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5 months ago
2024-07-10 3:44pm
v42
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5 months ago
2024-06-26 5:01am
v35
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6 months ago
2024-06-26 4:55am
v34
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6 months ago
2024-06-26 4:36am
v33
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6 months ago
2024-06-26 4:36am
v32
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6 months ago
2024-06-23 2:34pm
v28
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6 months ago
2024-06-23 2:33pm
v27
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6 months ago
2024-06-23 2:29pm
v25
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6 months ago
2024-06-23 2:24pm
v22
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6 months ago
2024-06-23 2:22pm
v21
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6 months ago
2024-06-23 1:12pm
v20
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6 months ago
2024-06-23 1:12pm
v19
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6 months ago
2024-06-23 1:11pm
v18
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6 months ago
2024-06-23 1:07pm
v17
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6 months ago
2024-06-23 11:32am
v16
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6 months ago
2024-06-23 11:21am
v15
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6 months ago
2024-06-22 5:57am
v14
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6 months ago
2024-06-21 5:04am
v13
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6 months ago
2024-06-16 9:43am
v12
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6 months ago
2024-06-16 5:48am
v11
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6 months ago
2024-06-15 6:57pm
v10
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6 months ago
2024-06-13 11:16am
v9
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6 months ago
2024-06-13 11:01am
v8
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6 months ago
2024-06-13 10:47am
v7
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6 months ago
2024-06-11 8:08pm
v5
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6 months ago
2024-06-11 8:01pm
v4
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6 months ago
2024-06-03 12:22pm
v3
·
7 months ago
2024-06-03 9:53am
v2
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7 months ago
2024-06-03 12:54am
v1
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7 months ago
v7
2024-06-13 10:47am
Generated on
Jun 13, 2024
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.
1235 Total Images
View All ImagesDataset Split
Train
Set
82%
1014Images
Valid
Set
10%
126Images
Test
Set
8%
95Images
Preprocessing
Auto-Orient:
Applied
Resize:
Stretch to 640x480
Augmentations
Outputs per training example:
3
Blur:
Up to 0.7px
Noise:
Up to 0.46% of pixels
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