Dataset Versions

2023-09-19 4:06pm

Generated on Sep 19, 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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156 Total Images

View All Images

Dataset Split

Train Set 87%

135Images

Valid Set 10%

16Images

Test Set 3%

5Images

Preprocessing

Auto-Orient: Applied

Resize: Stretch to 640x640

Augmentations

Outputs per training example: 3

Flip: Horizontal

Shear: ±15° Horizontal, ±15° Vertical

Grayscale: Apply to 10% of images

Hue: Between -25° and +25°

Exposure: Between -25% and +25%

Noise: Up to 5% of pixels

Bounding Box: 90° Rotate: Clockwise, Counter-Clockwise

Bounding Box: Noise: Up to 5% of pixels

Similar Projects

Annotations

Group:

'con_casco', 'sin_casco'

hard_hat_workers970.png

640x640

0.41MP

Updated May 28, 55687

8:49AM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient

Applied

Resize

Stretch to 640x640

90° Rotate

Applied Per Bounding Box

Noise

Applied Per Bounding Box

Shear

X: 0°
Y: -10°

Hue

-13°

Exposure

Noise

1.75%

Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "tni9AzJCRDI65drTvmmb"
    ],
    "destination": "3b8e4ea7b29918428cc3ef38c01fa927",
    "height": 640,
    "id": "oXYls6NLgQ92AWrmuh4g",
    "label": [],
    "labels": [],
    "name": "hard_hat_workers970.png",
    "numSteps": 8,
    "owner": "SloWvxclQGWIaQSQVPNO8sna4NL2",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Stretch to\",640,640]",
        "ninety:[[0]]",
        "noise:[[3,389071]]",
        "shear:[0,-10]",
        "hue:[-13]",
        "exposure:[1]",
        "noise:[1.75,870157]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Stretch to 640x640"
        },
        {
            "name": "90° Rotate",
            "value": "Applied Per Bounding Box"
        },
        {
            "name": "Noise",
            "value": "Applied Per Bounding Box"
        },
        {
            "name": "Shear",
            "value": "X: 0°<br/>Y: -10°"
        },
        {
            "name": "Hue",
            "value": "-13°"
        },
        {
            "name": "Exposure",
            "value": "1%"
        },
        {
            "name": "Noise",
            "value": "1.75%"
        }
    ],
    "source": "oXYls6NLgQ92AWrmuh4g",
    "split": "train",
    "split.tni9AzJCRDI65drTvmmb.2": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",640,640]\",\n    \"ninety:[[0]]\",\n    \"noise:[[3,389071]]\",\n    \"shear:[0,-10]\",\n    \"hue:[-13]\",\n    \"exposure:[1]\",\n    \"noise:[1.75,870157]\"\n]",
    "updated": 1695157577383,
    "updatedDate": "May 28, 55687",
    "updatedTime": "8:49AM",
    "updatedTimezone": "+00:00",
    "versions": [
        "tni9AzJCRDI65drTvmmb/2"
    ],
    "width": 640
}

Annotation Data

{
    "boxes": [
        {
            "label": "-con_casco-",
            "x": 356.5,
            "y": 236.73623949695093,
            "width": 40.875,
            "height": 31.380697645335545
        }
    ],
    "height": 640,
    "key": "hard_hat_workers970.png",
    "width": 640
}

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