Dataset Versions

Try Pre-Trained Model

2023-06-06 5:34pm

2023-06-06 5:30pm

v2

2023-06-06 5:34pm

Generated on Jun 6, 2023

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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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1577 Total Images

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Dataset Split

Train Set 92%

1453Images

Valid Set 4%

62Images

Test Set 4%

62Images

Preprocessing

Auto-Orient: Applied

Augmentations

Outputs per training example: 3

Brightness: Between -12% and +12%

Blur: Up to 2.5px

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ToothDataset-2

Annotate

11 / 12

Show/hide annotations(H)

train

Labels

Attributes

Raw Data

Annotations

Group:

Tooth

CLASSES

LAYERS

Gigi 11

1

Gigi 12

1

Gigi 13

1

Gigi 14

1

Gigi 15

1

Gigi 16

1

Gigi 17

1

Gigi 21

1

Gigi 22

1

Gigi 23

1

Gigi 24

1

Gigi 25

1

Gigi 26

1

Gigi 27

1

Gigi 31

1

Gigi 32

1

Gigi 33

1

Gigi 34

1

Gigi 35

1

Gigi 36

1

Gigi 37

1

Gigi 41

1

Gigi 42

1

Gigi 43

1

Gigi 44

1

Gigi 45

1

Gigi 46

1

Gigi 47

1

Unused Classes

Gigi 18

Gigi 28

Gigi 38

Gigi 48

Tags

No Tags Applied

Type and select tags below to add them to the image.

Attributes

YENI-PUSPITASARI_28_NOV.jpg

1094x565

0.62MP

Updated Sep 21, 55398

1:56PM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient

Applied

Annotation History

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Raw Data

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        "Gigi 18": 488,
        "Gigi 21": 603,
        "Gigi 22": 600,
        "Gigi 23": 603,
        "Gigi 24": 598,
        "Gigi 25": 596,
        "Gigi 26": 592,
        "Gigi 27": 597,
        "Gigi 28": 473,
        "Gigi 31": 606,
        "Gigi 32": 604,
        "Gigi 33": 603,
        "Gigi 34": 593,
        "Gigi 35": 585,
        "Gigi 36": 577,
        "Gigi 37": 585,
        "Gigi 38": 492,
        "Gigi 41": 608,
        "Gigi 42": 607,
        "Gigi 43": 604,
        "Gigi 44": 598,
        "Gigi 45": 591,
        "Gigi 46": 569,
        "Gigi 47": 597,
        "Gigi 48": 506
    },
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    "numSteps": 1,
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}

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