EgoHands Dataset specific

Export Created

4 years ago

December 09, 2020

Export Size

4800 images

Annotations

hands

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
38403840

Valid
480480

Test
480480

Preprocessing Options

Applied to all images in dataset

Auto-Orient

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

Augmentation Options

Randomly applied to images in your training set

No augmentation steps were applied.

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

EgoHands Public

Annotate

8 / 45

Show/hide annotations(H)

train

Labels

Attributes

Raw Data

Annotations

Group:

hands

Classes

Layers

myleft

1

myright

1

yourleft

1

yourright

1

Unused Classes

hand

Tags

No Tags Applied

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

Attributes

CHESS_LIVINGROOM_T_H_frame_0436.jpg

1280x720

0.92MP

Updated Dec 21, 52910

6:25AM

GMT+00:00

Generated by Roboflow

Training Set

Train 80%

Valid 10%

Test 10%

Transforms

Auto-Orient

Applied

Annotation History

Loading...

Raw Data

Source Data

                            {
    "camera": "Generated by Roboflow",
    "datasets": [
        "TBMuP6PVVB5CvjDufgYR"
    ],
    "destination": "5348dcda498ae06d97166e2642bdad7a",
    "height": 720,
    "id": "DBKvfr4CgwpkYGIdeZTD",
    "label": [],
    "labels": [],
    "name": "CHESS_LIVINGROOM_T_H_frame_0436.jpg",
    "numSteps": 1,
    "owner": "5w20VzQObTXjJhTjq6kad9ubrm33",
    "preprocessing": [
        "auto-orient"
    ],
    "preprocessingParsed": [
        {
            "name": "Auto-Orient",
            "value": "Applied"
        }
    ],
    "source": "DBKvfr4CgwpkYGIdeZTD",
    "split": "train",
    "split.TBMuP6PVVB5CvjDufgYR.1": "train",
    "status": "generated",
    "transforms": "[\n    \"auto-orient\"\n]",
    "updated": 1607541747901,
    "updatedDate": "Dec 21, 52910",
    "updatedTime": "6:25AM",
    "updatedTimezone": "+00:00",
    "versions": [
        "TBMuP6PVVB5CvjDufgYR/1"
    ],
    "width": 1280
}

Annotation Data

{
    "boxes": [
        {
            "label": "myleft",
            "x": 191,
            "y": 329,
            "width": 380,
            "height": 288
        },
        {
            "label": "myright",
            "x": 707.5,
            "y": 680.5,
            "width": 375,
            "height": 77
        },
        {
            "label": "yourleft",
            "x": 937,
            "y": 332,
            "width": 194,
            "height": 206
        },
        {
            "label": "yourright",
            "x": 111,
            "y": 386,
            "width": 118,
            "height": 68
        }
    ],
    "height": 720,
    "key": "CHESS_LIVINGROOM_T_H_frame_0436.jpg",
    "width": 1280
}

Annotation Editor

Delete

Save (Enter)

Smart Polygon

Click inside to remove area or outside to expand.

Undo

Redo

Simplify

Simple Complex

Delete

Finish (Enter)

90%

Reset