Dataset Versions

2024-06-25 10:23am

Generated on Jun 25, 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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1499 Total Images

View All Images

Dataset Split

Train Set 70%

1049Images

Valid Set 20%

300Images

Test Set 10%

150Images

Preprocessing

Auto-Orient: Applied

Resize: Fill (with center crop) in 640x640

Augmentations

No augmentations were applied.

Similar Projects

Annotations

Group: litter

Unlabeled litter

Unused Classes

Aerosol

Aluminium blister pack

Aluminium foil

Battery

Cigarette

Clear plastic bottle

Disposable food container

Disposable plastic cup

Drink can

Drink carton

Egg carton

Foam cup

Foam food container

Food Can

Food waste

Garbage bag

Glass bottle

Glass cup

Glass jar

Meal carton

Metal bottle cap

Metal lid

Normal paper

Other carton

Other plastic

Other plastic bottle

Other plastic container

Other plastic cup

Other plastic wrapper

Paper bag

Paper cup

Paper straw

Plastic bottle cap

Plastic film

Plastic glooves

Plastic lid

Plastic straw

Plastic utensils

Polypropylene bag

Pop tab

Rope & strings

Scrap metal

Shoe

Single-use carrier bag

Six pack rings

Spread tub

Squeezable tube

Styrofoam piece

Tissues

Toilet tube

Tupperware

Wrapping paper

Attributes

IMG_4997.JPG

640x640

0.41MP

Updated Oct 17, 56452

11:43PM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient

Applied

Resize

Fill (with center crop) in 640x640

Raw Data

Source Data

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    "camera": "Generated by Roboflow",
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    ],
    "destination": "c7060af595c6733fda26563d3134deef",
    "height": 640,
    "id": "vFUzqCMNc0M4AE2RUMNX",
    "label": [],
    "labels": [],
    "name": "IMG_4997.JPG",
    "numSteps": 2,
    "owner": "C6d9KDFfq9bn4EMF5yYijfj8x712",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Fill (with center crop) in\",640,640]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Fill (with center crop) in 640x640"
        }
    ],
    "source": "vFUzqCMNc0M4AE2RUMNX",
    "split": "train",
    "split.OJk3aub31dSKQj2TeFSm.1": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Fill (with center crop) in\\\",640,640]\"\n]",
    "updated": 1719311010212,
    "updatedDate": "Oct 17, 56452",
    "updatedTime": "11:43PM",
    "updatedTimezone": "+00:00",
    "versions": [
        "OJk3aub31dSKQj2TeFSm/1"
    ],
    "width": 640
}

Annotation Data

{
    "boxes": [
        {
            "type": "polygon",
            "label": "Unlabeled litter",
            "x": 266.39473699999996,
            "y": 622,
            "width": 62.789473999999984,
            "height": 36,
            "points": [
                [
                    297.789474,
                    640
                ],
                [
                    292,
                    635
                ],
                [
                    251,
                    604
                ],
                [
                    235,
                    621
                ],
                [
                    236,
                    625
                ],
                [
                    251,
                    636
                ],
                [
                    257.666667,
                    640
                ],
                [
                    297.789474,
                    640
                ]
            ]
        }
    ],
    "height": 640,
    "key": "IMG_4997.JPG",
    "width": 640
}

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