Dataset Versions

2022-04-16 11:17pm

2022-04-16 7:56pm

2022-04-15 6:44am

2022-04-14 2:54am

clutter-dataset-2

v6

final_140

Generated on Apr 16, 2022

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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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140 Total Images

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Dataset Split

Train Set 82%

115Images

Valid Set 8%

11Images

Test Set 10%

14Images

Preprocessing

Auto-Orient: Applied

Resize: Stretch to 640x640

Augmentations

No augmentations were applied.

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clutter-dataset-2

Annotate

11 / 12

Show/hide annotations(H)

train

Labels

Attributes

Raw Data

Annotations

Group:

objects

CLASSES

LAYERS

chair

2

keyboard

1

mouse

1

tvmonitor

1

Unused Classes

backpack

bed

bicycle

bottle

bowl

cell phone

clock

couch

cup

frying pan

handbag

landline

laptop

penholder

person

potted plant

sunglasses

tablefan

Tags

No Tags Applied

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

Attributes

63.jpg

640x640

0.41MP

Updated Apr 16, 2022

7:36PM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient	Applied
Resize	Stretch to 640x640

Annotation History

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Raw Data

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    "height": 640,
    "id": "1J7tbq7UQNfpFKKUhmAH",
    "label": [],
    "labels": [],
    "name": "63.jpg",
    "numSteps": 2,
    "owner": "rNzRkyad4VeYLqLNdMgQuHvmX3K3",
    "preprocessing": [
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    "preprocessingParsed": [
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            "value": "Applied"
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            "name": "Resize",
            "value": "Stretch to 640x640"
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    ],
    "source": "1J7tbq7UQNfpFKKUhmAH",
    "split": "train",
    "split.vZNhITkqtCkuVvA0ffcb.4": "train",
    "split.vZNhITkqtCkuVvA0ffcb.5": "train",
    "split.vZNhITkqtCkuVvA0ffcb.6": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",640,640]\"\n]",
    "updated": {
        "_seconds": 1650137760,
        "_nanoseconds": 834000000
    },
    "updatedDate": "Apr 16, 2022",
    "updatedTime": "7:36PM",
    "updatedTimezone": "+00:00",
    "versions": [
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        "vZNhITkqtCkuVvA0ffcb/5",
        "vZNhITkqtCkuVvA0ffcb/6"
    ],
    "width": 640
}

{
    "boxes": [
        {
            "label": "tvmonitor",
            "x": 436.5,
            "y": 257.5,
            "width": 74,
            "height": 106.5
        },
        {
            "label": "mouse",
            "x": 505,
            "y": 349,
            "width": 25,
            "height": 20
        },
        {
            "label": "keyboard",
            "x": 453,
            "y": 351,
            "width": 94,
            "height": 35
        },
        {
            "label": "chair",
            "x": 558,
            "y": 416.5,
            "width": 163,
            "height": 281
        },
        {
            "label": "chair",
            "x": 312.5,
            "y": 450,
            "width": 123,
            "height": 259
        }
    ],
    "height": 640,
    "key": "63.jpg",
    "width": 640
}

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