Dataset Versions

v13

2023-12-07 10:23am

Generated on Dec 7, 2023

Download Dataset

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.

530 Total Images

View All Images

Dataset Split

Train Set 81%

430Images

Valid Set 10%

55Images

Test Set 8%

45Images

Preprocessing

Auto-Orient: Applied

Resize: Fit within 608x608

Augmentations

No augmentations were applied.

Similar Projects

Annotations

Group:

pieces

MITA_30_NOV.jpg

608x319

0.19MP

Updated Sep 6, 55901

3:47AM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient

Applied

Resize

Fit within 608x608

Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "LtwC0w0HdK2jdw8Uc1ZE"
    ],
    "destination": "372716f75f95e9052ccc8c5f3bc67148",
    "height": 319,
    "id": "0SSyg5doyWzy66O0WuYq",
    "label": [],
    "labels": [],
    "name": "MITA_30_NOV.jpg",
    "numSteps": 2,
    "owner": "0qVdubn6SJddvDLW7kZLzHzbNdE3",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Fit within\",608,608]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Fit within 608x608"
        }
    ],
    "source": "0SSyg5doyWzy66O0WuYq",
    "split": "train",
    "split.LtwC0w0HdK2jdw8Uc1ZE.12": "train",
    "split.LtwC0w0HdK2jdw8Uc1ZE.13": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Fit within\\\",608,608]\"\n]",
    "updated": 1701919396051,
    "updatedDate": "Sep 6, 55901",
    "updatedTime": "3:47AM",
    "updatedTimezone": "+00:00",
    "user_tags": [],
    "versions": [
        "LtwC0w0HdK2jdw8Uc1ZE/12",
        "LtwC0w0HdK2jdw8Uc1ZE/13"
    ],
    "width": 608
}

Annotation Data

{
    "boxes": [
        {
            "label": "18",
            "x": 147,
            "y": 130,
            "width": 43,
            "height": 39
        },
        {
            "label": "17",
            "x": 158,
            "y": 155,
            "width": 37,
            "height": 54
        },
        {
            "label": "16",
            "x": 187,
            "y": 158,
            "width": 33,
            "height": 58
        },
        {
            "label": "15",
            "x": 213,
            "y": 162,
            "width": 22,
            "height": 63
        },
        {
            "label": "14",
            "x": 235,
            "y": 168,
            "width": 25,
            "height": 59
        },
        {
            "label": "13",
            "x": 254,
            "y": 168,
            "width": 22,
            "height": 60
        },
        {
            "label": "12",
            "x": 279,
            "y": 170,
            "width": 24,
            "height": 57
        },
        {
            "label": "11",
            "x": 299,
            "y": 168,
            "width": 22,
            "height": 63
        },
        {
            "label": "21",
            "x": 324,
            "y": 171,
            "width": 24,
            "height": 58
        },
        {
            "label": "22",
            "x": 345,
            "y": 171,
            "width": 19,
            "height": 55
        },
        {
            "label": "23",
            "x": 366,
            "y": 168,
            "width": 22,
            "height": 67
        },
        {
            "label": "24",
            "x": 384,
            "y": 168,
            "width": 27,
            "height": 60
        },
        {
            "label": "25",
            "x": 402,
            "y": 160,
            "width": 25,
            "height": 61
        },
        {
            "label": "26",
            "x": 430,
            "y": 157,
            "width": 31,
            "height": 62
        },
        {
            "label": "27",
            "x": 462,
            "y": 153,
            "width": 31,
            "height": 54
        },
        {
            "label": "28",
            "x": 469,
            "y": 126,
            "width": 41,
            "height": 39
        },
        {
            "label": "38",
            "x": 490,
            "y": 190,
            "width": 50,
            "height": 40
        },
        {
            "label": "37",
            "x": 459,
            "y": 211,
            "width": 48,
            "height": 54
        },
        {
            "label": "36",
            "x": 422,
            "y": 221,
            "width": 46,
            "height": 60
        },
        {
            "label": "35",
            "x": 392,
            "y": 225,
            "width": 25,
            "height": 54
        },
        {
            "label": "34",
            "x": 372,
            "y": 230,
            "width": 25,
            "height": 57
        },
        {
            "label": "33",
            "x": 353,
            "y": 235,
            "width": 18,
            "height": 61
        },
        {
            "label": "32",
            "x": 333,
            "y": 231,
            "width": 19,
            "height": 53
        },
        {
            "label": "31",
            "x": 317,
            "y": 232,
            "width": 15,
            "height": 52
        },
        {
            "label": "41",
            "x": 300,
            "y": 230,
            "width": 16,
            "height": 48
        },
        {
            "label": "42",
            "x": 284,
            "y": 231,
            "width": 19,
            "height": 52
        },
        {
            "label": "43",
            "x": 265,
            "y": 236,
            "width": 20,
            "height": 60
        },
        {
            "label": "44",
            "x": 247,
            "y": 229,
            "width": 24,
            "height": 56
        },
        {
            "label": "45",
            "x": 225,
            "y": 227,
            "width": 25,
            "height": 60
        },
        {
            "label": "46",
            "x": 192,
            "y": 221,
            "width": 54,
            "height": 62
        },
        {
            "label": "47",
            "x": 157,
            "y": 209,
            "width": 51,
            "height": 54
        },
        {
            "label": "48",
            "x": 130,
            "y": 190,
            "width": 41,
            "height": 39
        }
    ],
    "height": 319,
    "key": "MITA_30_NOV.jpg",
    "width": 608
}

Deteksi Gigi