Segmonto Image Dataset
Versions
2024-05-03 10:36am
v27
May 3, 2024
2024-02-19 3:15pm
v26
Feb 19, 2024
2023-12-18 8:09am
v25
Dec 18, 2023
2023-12-16 8:19am
v24
Dec 16, 2023
2023-12-15 8:41pm
v23
Dec 15, 2023
2023-12-11 11:19am
v22
Dec 11, 2023
2023-11-27 8:30am
v21
Nov 27, 2023
2023-11-27 8:29am
v20
Nov 27, 2023
2023-11-22 8:41am
v19
Nov 22, 2023
2023-11-15 3:55pm
v18
Nov 15, 2023
2023-11-15 2:33pm
v17
Nov 15, 2023
2023-11-14 4:54pm
v16
Nov 14, 2023
2023-11-13 6:22pm
v15
Nov 13, 2023
2023-11-09 8:29am
v14
Nov 9, 2023
2023-11-03 12:56pm
v13
Nov 3, 2023
Segmonto12
v12
Oct 24, 2023
2023-10-23 5:39pm
v11
Oct 23, 2023
2023-10-23 3:07pm
v10
Oct 23, 2023
2023-10-23 9:55am
v9
Oct 23, 2023
2023-10-23 9:21am
v8
Oct 23, 2023
2023-10-18 10:52am
v7
Oct 18, 2023
2023-10-18 8:43am
v6
Oct 18, 2023
2023-10-17 6:21pm
v5
Oct 17, 2023
2023-10-16 8:40am
v4
Oct 16, 2023
2023-10-13 11:23am
v3
Oct 13, 2023
2023-10-13 11:23am
v2
Oct 13, 2023
2023-10-12 10:55am
v1
Oct 12, 2023
v17
2023-11-15 2:33pm
Generated on Nov 15, 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.
5540 Total Images
View All Images
Dataset Split
Train Set 94%
5202Images
Valid Set 5%
272Images
Test Set 1%
66Images
Preprocessing
Modify Classes: 3 remapped, 0 dropped
Augmentations
Outputs per training example: 3
Rotation: Between -3° and +3°
Blur: Up to 1.5px
Noise: Up to 2% of pixels
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