Downloads

Anki Vector Robot Dataset Dataset v5 (Resize + Grayscale + Rotate + Blur + BB optimizations)

Export Created

5 years ago

September 18, 2020

Export Size

727 images

Annotations

vectorCompleteDataset

Available Download Formats

COCO JSON
COCO JSON annotations are used with EfficientDet Pytorch and Detectron 2.
COCO-MMDetection
COCO-MMDetection JSON annotations are used with MMDetection.
CreateML JSON
CreateML JSON format is used with Apple's CreateML and Turi Create tools.
PaliGemma JSONL
PaliGemma format is used with Google's Multimodal Vision Model.
Pascal VOC XML
Common XML annotation format for local data munging (pioneered by ImageNet).
YOLO Darknet TXT
Darknet TXT annotations used with YOLO Darknet (both v3 and v4) and YOLOv3 PyTorch.
YOLO v3 Keras TXT
TXT annotations used with YOLOv3 Keras.
YOLO v4 PyTorch
Darknet TXT annotations used with YOLOv4 PyTorch (deprecated).
Scaled-YOLOv4
Scaled YOLOv4 TXT annotations used with Scaled-YOLOv4.
YOLOv5-OBB
YOLOv5 Oriented Bounding Boxes TXT annotations used with YOLOv5-OBB.
MT-YOLOv6
MT-YOLOv6 TXT annotations used with meituan/YOLOv6.
YOLO v5 PyTorch
TXT annotations and YAML config used with YOLOv5.
YOLO v7 PyTorch
TXT annotations and YAML config used with YOLOv7.
YOLOv8
TXT annotations and YAML config used with YOLOv8.
YOLOv8-OBB
YOLOv8 Oriented Bounding Boxes TXT annotations used with YOLOv8-OBB.
YOLOv9
TXT annotations and YAML config used with YOLOv9.
YOLOv11
TXT annotations and YAML config used with YOLOv11.
YOLOv12 TXT annotations and YAML config used with YOLOv12
Tensorflow Object Detection CSV
CSV format used with Tensorflow (usually converted before training so you probably want to export as a TFRecord instead unless you need to inspect the human-readable CSV).
RetinaNet Keras CSV
A custom CSV format used by Keras implementation of RetinaNet.
Multiclass Classification
Converts your object detection dataset into a classification dataset CSV.
OpenAI CLIP Classification
Converts your object detection dataset a classification dataset for use with OpenAI CLIP.
Tensorflow TFRecord
TFRecord binary format used for both Tensorflow 1.5 and Tensorflow 2.0 Object Detection models.

Preview

Train/Test Split

Your images are split at upload time. Learn more.

Train
636636
Valid
6161
Test
3030

Preprocessing Options

Applied to all images in dataset

Auto-Orient

Resize

Stretch to 416x416

Grayscale

Auto-Adjust Contrast

Using Contrast Stretching

Preprocessing can decrease training time and increase inference speed. Learn more on our blog.

Augmentation Output

Save

For each image in your training set, how many augmented versions do you want to generate?

(Starter Plan Max: 3)

Size: 727 images.

Augmentation Options

Randomly applied to images in your training set

Rotation

Between -5° and +5°

Blur

Up to 0.25px

Noise

Up to 5% of pixels

Bounding Box: Brightness

Between -25% and +25%

Augmentations create new training examples for your model to learn from. Learn more on our blog.

vectorCompleteDataset
Annotate
36 / 45
Show/hide annotations(H)
train
Labels
Attributes
Raw Data

Annotations

Group: vectorCompleteDataset
 
vector
1

Attributes

picture146.jpeg

416x416
0.17MP

Updated Jan 9, 52685

2:54AM
GMT+00:00

Generated by Roboflow

Training Set

Train 80%
Valid 13%
Test 6%

Transforms

Auto-Orient Applied
Resize Stretch to 416x416
Grayscale Applied
Auto-Adjust Contrast Contrast Stretching
Brightness Applied Per Bounding Box
Rotation -2°
Blur 0.25px
Noise 1%

Annotation History

Loading...

Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "iFhPxc4VeT51iztFZWMe"
    ],
    "destination": "60ce7ae995dc1f3f10067289323b3a8d",
    "height": 416,
    "id": "hY1fldZAgcE59KgQskss",
    "label": [],
    "labels": [],
    "name": "picture146.jpeg",
    "numSteps": 8,
    "owner": "jLZjGISePFfAoa5j83iVtXvHvE82",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Stretch to\",416,416]",
        "grayscale",
        "auto-contrast:[\"Contrast Stretching\"]",
        "brightness:[[23]]",
        "rotate:[-2]",
        "blur:[0.25]",
        "noise:[1,860255]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Stretch to 416x416"
        },
        {
            "name": "Grayscale",
            "value": "Applied"
        },
        {
            "name": "Auto-Adjust Contrast",
            "value": "Contrast Stretching"
        },
        {
            "name": "Brightness",
            "value": "Applied Per Bounding Box"
        },
        {
            "name": "Rotation",
            "value": "-2°"
        },
        {
            "name": "Blur",
            "value": "0.25px"
        },
        {
            "name": "Noise",
            "value": "1%"
        }
    ],
    "source": "hY1fldZAgcE59KgQskss",
    "split": "train",
    "split.iFhPxc4VeT51iztFZWMe.5": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",416,416]\",\n    \"grayscale\",\n    \"auto-contrast:[\\\"Contrast Stretching\\\"]\",\n    \"brightness:[[23]]\",\n    \"rotate:[-2]\",\n    \"blur:[0.25]\",\n    \"noise:[1,860255]\"\n]",
    "updated": 1600411575246,
    "updatedDate": "Jan 9, 52685",
    "updatedTime": "2:54AM",
    "updatedTimezone": "+00:00",
    "versions": [
        "iFhPxc4VeT51iztFZWMe/5"
    ],
    "width": 416
}

Annotation Data

{
    "boxes": [
        {
            "label": "vector",
            "x": 156.5,
            "y": 231,
            "width": 255,
            "height": 366
        }
    ],
    "height": 416,
    "key": "picture146.jpeg",
    "width": 416
}

Annotation Editor

Delete
Save (Enter)

Smart Polygon

Click inside to remove area or outside to expand.
Undo
Redo
Simplify
Simple Complex
Delete
Finish (Enter)
270%
Reset