Outdoor Rooftop Object Detection

Object Detection

Dataset Versions

2024-04-12 5:52pm

2024-04-12 5:40pm

2024-04-10 11:58am

2024-04-10 9:57am

2024-04-10 9:24am

2024-04-08 11:27am

2024-04-03_525_images

325_images_25-03

v2

2024-04-03_525_images

Generated on Apr 3, 2024

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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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1355 Total Images

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Dataset Split

Train Set 92%

1247Images

Valid Set 5%

74Images

Test Set 3%

34Images

Preprocessing

No preprocessing steps were applied.

Augmentations

Outputs per training example: 3

Flip: Horizontal

Brightness: Between -15% and +15%

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Outdoor Rooftop Object Detection

Annotate

2 / 12

Show/hide annotations(H)

train

Labels

Attributes

Raw Data

Annotations

Group:

Furniture

Classes

Layers

Outdoor Accent Chair

1

Outdoor Coffee Table

1

Outdoor Sofa

1

Unused Classes

Barstools

Firepit

Outdoor Chaise

Outdoor Dining Chairs

Outdoor Dining Table

Outdoor End Tables

Plants

Umbrella

Tags

No Tags Applied

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

Attributes

260.jpg

1500x1000

1.50MP

Updated Mar 21, 56226

8:55AM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Brightness

-12%

Annotation History

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Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "DeHbh2jPgwO5ouCcMnon"
    ],
    "destination": "f191f57eed1d7eedf1e07ff873a906b6",
    "height": 1000,
    "id": "orheu0zTsDG8CkPFltkT",
    "label": [],
    "labels": [],
    "name": "260.jpg",
    "numSteps": 1,
    "owner": "BF0FxFYAKmilGWfwZ1w2",
    "preprocessing": [
        "brightness:[-12]"
    ],
    "preprocessingParsed": [
        {
            "name": "Brightness",
            "value": "-12%"
        }
    ],
    "source": "orheu0zTsDG8CkPFltkT",
    "split": "train",
    "split.DeHbh2jPgwO5ouCcMnon.2": "train",
    "status": "generated",
    "transforms": "[\n    \"brightness:[-12]\"\n]",
    "updated": 1712160838544,
    "updatedDate": "Mar 21, 56226",
    "updatedTime": "8:55AM",
    "updatedTimezone": "+00:00",
    "versions": [
        "DeHbh2jPgwO5ouCcMnon/2"
    ],
    "width": 1500
}

Annotation Data

{
    "boxes": [
        {
            "label": "Outdoor Accent Chair",
            "x": 243,
            "y": 638,
            "width": 398,
            "height": 408
        },
        {
            "label": "Outdoor Coffee Table",
            "x": 761,
            "y": 721,
            "width": 366,
            "height": 178
        },
        {
            "label": "Outdoor Sofa",
            "x": 967,
            "y": 630,
            "width": 1046,
            "height": 360
        }
    ],
    "height": 1000,
    "key": "260.jpg",
    "width": 1500
}

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