---
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](https://falcon.duality.ai/secure/documentation?learnWelcome=true&sidebarMode=learn) to create data to be used for pose estimation on different objects. 

## Dataset Structure

The dataset has the following structure:
```plaintext
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
1. **Images**: RGB images of the object in `.png` format.
2. **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.
3. **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:
```plaintext
x y z qx qy qz qw
```
Example:
```plaintext
0.12 0.45 0.78 0.0 0.707 0.0 0.707
```

## Licensing
license: apache-2.0