metadata

license: apache-2.0
language:
  - en
pretty_name: Pose_Estimation
size_categories:
  - 1K<n<10K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
      - split: test
        path: data/test-*
dataset_info:
  features:
    - name: image
      dtype: image
    - name: label
      dtype: string
    - name: mask
      dtype: image
  splits:
    - name: train
      num_bytes: 13279441183.085424
      num_examples: 3385
    - name: test
      num_bytes: 3329559074.0245748
      num_examples: 847
  download_size: 16598689781
  dataset_size: 16609000257.109999

Pose Estimation Dataset

Overview

This dataset is designed for pose estimation tasks, focusing on determining the position and orientation of an object in 3D space. The dataset includes images, masks, and labels for both training and validation, making it suitable for machine learning applications in 3D object tracking and computer vision. This dataset was generated using Duality.ai simulation software: FalconEditor. Try FalconEditor today to create data to be used for pose estimation on different objects.

Dataset Structure

The dataset has the following structure:

pose_estimation_dataset/
|-- train/
|   |-- images/
|   |   |-- 000000000.png
|   |   |-- 000000001.png
|   |   |-- ...
|   |-- labels/
|   |   |-- 000000000.txt
|   |   |-- 000000001.txt
|   |   |-- ...
|   |-- masks/
|       |-- 000000000.png
|       |-- 000000001.png
|       |-- ...
|-- val/
    |-- images/
    |   |-- 000000000.png
    |   |-- 000000001.png
    |   |-- ...
    |-- labels/
    |   |-- 000000000.txt
    |   |-- 000000001.txt
    |   |-- ...
    |-- masks/
        |-- 000000000.png
        |-- 000000001.png
        |-- ...

Components

Images: RGB images of the object in .png format.
Labels: Text files (.txt) containing 3D pose annotations. Each label file corresponds to an image and contains the following information:
- Three position values [x, y, z] representing the object's location in 3D space.
- Four quaternion values [qx, qy, qz, qw] representing the object's orientation in 3D space.
Masks: Binary masks (.png) highlighting the object’s silhouette in the image.

Usage

To use this dataset, load the images, labels, and masks for your pose estimation pipeline. Ensure that the corresponding image, label, and mask files share the same base filename.

Example

If you have train/images/image_1.png, the corresponding files will be:

train/labels/image_1.txt
train/masks/image_1.png

Label Format

Each .txt label file contains a single line in the following format:

x y z qx qy qz qw

Example:

0.12 0.45 0.78 0.0 0.707 0.0 0.707

Licensing

license: apache-2.0