MobileScaffoldingCheck

Object Detection

Dataset Versions

Try Pre-Trained Model

2023-11-25 5:36pm

2023-11-22 4:13pm

2023-11-20 2:46pm

2023-11-09 1:45pm

2023-11-09 12:13pm

2023-11-08 1:26pm

2023-10-30 7:27pm

v8

2023-11-25 5:36pm

Generated on Nov 25, 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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12672 Total Images

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Dataset Split

Train Set 92%

11706Images

Valid Set 4%

483Images

Test Set 4%

483Images

Preprocessing

Auto-Orient: Applied

Resize: Fit (black edges) in 640x640

Augmentations

Outputs per training example: 3

Flip: Horizontal

Hue: Between -25° and +25°

Saturation: Between -25% and +25%

Brightness: Between -25% and +25%

Exposure: Between -25% and +25%

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MobileScaffoldingCheck

Annotate

1 / 13

Show/hide annotations(H)

train

Labels

Attributes

Raw Data

Annotations

Group:

MobileScaffolding

Classes

Layers

mobile_scaffold_no_outtrigger

1

worker_with_helmet

1

Unused Classes

Missing Guardrail

mobile_scaffold_outtrigger

worker_without_helmet

Tags

No Tags Applied

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

Attributes

20231107_152228_488.jpg

640x640

0.41MP

Updated Jun 2, 55869

6:42PM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient	Applied
Resize	Fit (black edges) in 640x640

Annotation History

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Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "zp7u3E1w79MW3AmBHjQe"
    ],
    "destination": "2fef1c61ae5e039fe0eb4669f40d2bb2",
    "height": 640,
    "id": "NwGD96YBbY0cJI8u9Hyg",
    "label": [],
    "labels": [],
    "name": "20231107_152228_488.jpg",
    "numSteps": 2,
    "owner": "R1OvQGm0RCEm6241UyAW",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Fit (black edges) in\",640,640]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Fit (black edges) in 640x640"
        }
    ],
    "source": "NwGD96YBbY0cJI8u9Hyg",
    "split": "train",
    "split.zp7u3E1w79MW3AmBHjQe.3": "train",
    "split.zp7u3E1w79MW3AmBHjQe.5": "train",
    "split.zp7u3E1w79MW3AmBHjQe.6": "train",
    "split.zp7u3E1w79MW3AmBHjQe.7": "train",
    "split.zp7u3E1w79MW3AmBHjQe.8": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Fit (black edges) in\\\",640,640]\"\n]",
    "updated": 1700901398521,
    "updatedDate": "Jun 2, 55869",
    "updatedTime": "6:42PM",
    "updatedTimezone": "+00:00",
    "versions": [
        "zp7u3E1w79MW3AmBHjQe/3",
        "zp7u3E1w79MW3AmBHjQe/5",
        "zp7u3E1w79MW3AmBHjQe/6",
        "zp7u3E1w79MW3AmBHjQe/7",
        "zp7u3E1w79MW3AmBHjQe/8"
    ],
    "width": 640
}

Annotation Data

{
    "boxes": [
        {
            "label": "mobile_scaffold_no_outtrigger",
            "x": 350,
            "y": 329,
            "width": 244,
            "height": 348
        },
        {
            "label": "worker_with_helmet",
            "x": 386,
            "y": 189,
            "width": 88,
            "height": 168
        }
    ],
    "height": 640,
    "key": "20231107_152228_488.jpg",
    "width": 640
}

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