PPE Detection Using CV

Object Detection

Dataset Versions

Try Pre-Trained Model

2023-07-18 1:22pm

2023-07-12 2:48pm

2023-07-12 4:47pm

v3

2023-07-18 1:22pm

Generated on Jul 18, 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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2046 Total Images

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Dataset Split

Train Set 70%

1428Images

Valid Set 20%

403Images

Test Set 11%

215Images

Preprocessing

No preprocessing steps were applied.

Augmentations

No augmentations were applied.

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PPE Detection Using CV

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1 / 13

Show/hide annotations(H)

train

Labels

Attributes

Raw Data

Annotations

Group:

Safety-Equipment

Classes

Layers

goggles

1

Unused Classes

Person

helmet

no-goggles

no-helmet

no-vest

vest

Tags

No Tags Applied

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

Attributes

image_651.jpg

1000x472

0.47MP

Updated Nov 1, 55514

8:38PM

GMT+00:00

Generated by Roboflow

Training Set

Annotation History

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Raw Data

Source Data

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    "label": [],
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    "numSteps": 0,
    "owner": "gcFCorauPjQuNuj3lkYCkecdv5I3",
    "preprocessing": [],
    "preprocessingParsed": [],
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    "status": "generated",
    "transforms": "[]",
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    "updatedDate": "Nov 1, 55514",
    "updatedTime": "8:38PM",
    "updatedTimezone": "+00:00",
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    ],
    "width": 1000
}

Annotation Data

{
    "boxes": [
        {
            "label": "goggles",
            "x": 479.63,
            "y": 221.05,
            "width": 898.85,
            "height": 375.71
        }
    ],
    "height": 472,
    "key": "image_651.jpg",
    "width": 1000
}

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