Dataset Versions

newer version

Generated on Apr 19, 2022

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.

79 Total Images

View All Images

Dataset Split

Train Set 70%

55Images

Valid Set 19%

15Images

Test Set 11%

9Images

Preprocessing

Auto-Orient: Applied

Augmentations

No augmentations were applied.

Similar Projects

Annotations

Group:

Rings

CLASSES

LAYERS

caly

0_2022_04_19_08_24_01__2445_11_OK.jpg

1920x1080

2.07MP

Updated Oct 28, 54267

6:59PM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient

Applied

Raw Data

{
    "camera": "Generated by Roboflow",
    "datasets": [
        "1ZXMq7Cbpukg2xYAhenq"
    ],
    "destination": "8ed2165e725e4fff700c76884c425d22",
    "height": 1080,
    "id": "1DOZId3osc1nAyoryxwb",
    "label": [],
    "labels": [],
    "name": "0_2022_04_19_08_24_01__2445_11_OK.jpg",
    "numSteps": 1,
    "owner": "BRQTqMOME9Uf7qB7JsUup4YYXBr1",
    "preprocessing": [
        "auto-orient"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        }
    ],
    "source": "1DOZId3osc1nAyoryxwb",
    "split": "train",
    "split.1ZXMq7Cbpukg2xYAhenq.2": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\"\n]",
    "updated": 1650359905148,
    "updatedDate": "Oct 28, 54267",
    "updatedTime": "6:59PM",
    "updatedTimezone": "+00:00",
    "versions": [
        "1ZXMq7Cbpukg2xYAhenq/2"
    ],
    "width": 1920
}

{
    "boxes": [
        {
            "label": "caly",
            "x": 352.96,
            "y": 204.05,
            "width": 240.97000000000003,
            "height": 244.64
        },
        {
            "label": "caly",
            "x": 888.13,
            "y": 213.58,
            "width": 247.33999999999992,
            "height": 243.52000000000004
        },
        {
            "label": "caly",
            "x": 614.19,
            "y": 223.72,
            "width": 245.25,
            "height": 247.93
        },
        {
            "label": "caly",
            "x": 1159.21,
            "y": 232.38,
            "width": 244.07999999999993,
            "height": 243.63
        },
        {
            "label": "caly",
            "x": 1430.53,
            "y": 243.18,
            "width": 237.86000000000013,
            "height": 241.46000000000004
        },
        {
            "label": "caly",
            "x": 322.85,
            "y": 465.17,
            "width": 243.77999999999997,
            "height": 241.55000000000007
        },
        {
            "label": "caly",
            "x": 890.57,
            "y": 500.95,
            "width": 243.71000000000004,
            "height": 240.60000000000002
        },
        {
            "label": "caly",
            "x": 1159.2,
            "y": 501.6700000000001,
            "width": 244.1199999999999,
            "height": 242.03000000000003
        },
        {
            "label": "caly",
            "x": 612.49,
            "y": 502.02,
            "width": 242.19000000000005,
            "height": 242.72000000000003
        },
        {
            "label": "caly",
            "x": 329.94,
            "y": 748.19,
            "width": 238.36,
            "height": 243.67000000000007
        },
        {
            "label": "caly",
            "x": 592.55,
            "y": 755.77,
            "width": 243.29999999999995,
            "height": 245.07999999999993
        },
        {
            "label": "caly",
            "x": 874.59,
            "y": 762.96,
            "width": 244.41000000000008,
            "height": 241.95000000000005
        },
        {
            "label": "caly",
            "x": 1134.81,
            "y": 773.33,
            "width": 242.8699999999999,
            "height": 238.93000000000006
        }
    ],
    "height": 1080,
    "key": "0_2022_04_19_08_24_01__2445_11_OK.jpg",
    "width": 1920
}

Ring Detection