Dataset Versions

v3

final

Generated on Jun 10, 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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2371 Total Images

View All Images

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Dataset Split

Train Set 71%

1677Images

Valid Set 16%

384Images

Test Set 13%

310Images

Preprocessing

Auto-Orient: Applied

Resize: Stretch to 640x480

Grayscale: Applied

Filter Null: Require at least 90% of images to contain annotations.

Augmentations

Outputs per training example: 3

90° Rotate: Clockwise, Counter-Clockwise

Grayscale: Apply to 15% of images

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Theft Detection

Annotate

9 / 12

Show/hide annotations(H)

train

Labels

Attributes

Raw Data

Annotations

Group:

weapon-thieft

CLASSES

LAYERS

knife

1

Unused Classes

card

crowbar

hand

human

money

object

object-affected

object-non affected

pistol

smartphone

wallet

Tags

No Tags Applied

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

Attributes

DefenseKnifeAttack0456.jpg

640x480

0.31MP

Updated Dec 29, 56410

8:03AM

GMT+00:00

Generated by Roboflow

Training Set

Transforms

Auto-Orient	Applied
Resize	Stretch to 640x480
Grayscale	Applied
90° Rotate	Applied

Annotation History

Loading...

Raw Data

{
    "camera": "Generated by Roboflow",
    "classes": {
        "human": 123,
        "knife": 833,
        "monedero": 21,
        "money": 218,
        "object": 116,
        "object-affected": 90,
        "object-non affected": 2,
        "pistol": 70,
        "smartphone": 88,
        "tarjeta": 20
    },
    "datasets": [
        "fiRgfugOOMK1iy3EMPc9"
    ],
    "destination": "2fdc6d782249ac375a2ffe04f0c5ce77",
    "height": 480,
    "id": "miQMYEHUXk88NF9EpHDu",
    "label": [],
    "labels": [],
    "name": "DefenseKnifeAttack0456.jpg",
    "numSteps": 4,
    "owner": "mq4nsmFrRBTvPqxmLKInjPeM3Hw1",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Stretch to\",640,480]",
        "grayscale",
        "ninety:[0]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Stretch to 640x480"
        },
        {
            "name": "Grayscale",
            "value": "Applied"
        },
        {
            "name": "90° Rotate",
            "value": "Applied"
        }
    ],
    "source": "miQMYEHUXk88NF9EpHDu",
    "split": "train",
    "split.fiRgfugOOMK1iy3EMPc9.3": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",640,480]\",\n    \"grayscale\",\n    \"ninety:[0]\"\n]",
    "updated": 1717991798620,
    "updatedDate": "Dec 29, 56410",
    "updatedTime": "8:03AM",
    "updatedTimezone": "+00:00",
    "versions": [
        "fiRgfugOOMK1iy3EMPc9/3"
    ],
    "width": 640
}

{
    "boxes": [
        {
            "label": "knife",
            "x": 149,
            "y": 412,
            "width": 64,
            "height": 90
        }
    ],
    "height": 480,
    "key": "DefenseKnifeAttack0456.jpg",
    "width": 640
}

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