Downloads

Uno Cards Dataset v1

Export Created

5 years ago

June 29, 2020

Export Size

21582 images

Annotations

Card-Types

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
1888518885
Valid
17981798
Test
899899

Preprocessing Options

Applied to all images in dataset

Auto-Orient

Resize

Stretch to 416x416

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: 21582 images.

Augmentation Options

Randomly applied to images in your training set

Crop

0% Minimum Zoom, 20% Maximum Zoom

Rotation

Between -3° and +3°

Brightness

Between -25% and +25%

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

Uno Cards
Annotate
4 / 45
Show/hide annotations(H)
train
Labels
Attributes
Raw Data

Annotations

Group:
Card-Types

Classes

Layers

 
13
1
 
14
1
 
6
1

Unused Classes

0
1
10
11
12
2
3
4
5
7
8
9

Tags

No Tags Applied
Type and select tags below to add them to the image.

Attributes

272436905_jpg

384x384
0.15MP

Updated Dec 16, 52462

3:17AM
GMT+00:00

Generated by Roboflow

Training Set

Train 70%
Valid 20%
Test 10%

Transforms

Auto-Orient Applied
Resize Stretch to 416x416
Rotation 1°
Crop Keep 86%
Centered on 88%, 76%
Brightness -4%

Annotation History

Loading...

Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "UMuJj1MWsMgdDy4F3Rqp"
    ],
    "destination": "03ea3303770672e6efe06633e8b31cef",
    "height": 384,
    "id": "zyQcb7IlCnrrNIhqUgrj",
    "label": [],
    "labels": [],
    "name": "272436905_jpg",
    "numSteps": 5,
    "owner": "Ly2DeBzbwsemGd2ReHk4BFxy8683",
    "preprocessing": [
        "auto-orient",
        "resize:[\"Stretch to\",416,416]",
        "rotate:[1]",
        "crop:[86,0.876079,0.759147]",
        "brightness:[-4]"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        },
        {
            "name": "Resize",
            "value": "Stretch to 416x416"
        },
        {
            "name": "Rotation",
            "value": "1°"
        },
        {
            "name": "Crop",
            "value": "Keep 86%<br />Centered on 88%, 76%"
        },
        {
            "name": "Brightness",
            "value": "-4%"
        }
    ],
    "source": "zyQcb7IlCnrrNIhqUgrj",
    "split": "train",
    "split.UMuJj1MWsMgdDy4F3Rqp.1": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\",\n    \"resize:[\\\"Stretch to\\\",416,416]\",\n    \"rotate:[1]\",\n    \"crop:[86,0.876079,0.759147]\",\n    \"brightness:[-4]\"\n]",
    "updated": 1593403845478,
    "updatedDate": "Dec 16, 52462",
    "updatedTime": "3:17AM",
    "updatedTimezone": "+00:00",
    "versions": [
        "UMuJj1MWsMgdDy4F3Rqp/1"
    ],
    "width": 384
}

Annotation Data

{
    "boxes": [
        {
            "label": "14",
            "x": 261,
            "y": 213,
            "width": 28,
            "height": 21
        },
        {
            "label": "13",
            "x": 276,
            "y": 227.5,
            "width": 17,
            "height": 16
        },
        {
            "label": "6",
            "x": 292.5,
            "y": 259.5,
            "width": 25,
            "height": 23
        }
    ],
    "height": 384,
    "key": "272436905_jpg.rf.96125e01c0ca749a4b546ae0f5ed57c6.jpg",
    "width": 384
}

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