File size: 2,850 Bytes
9409728 f2ff56a 25b4a2e f2ff56a 82b7a53 d401d5d f2ff56a 82b7a53 d401d5d f2ff56a 29e3890 25b4a2e 29e3890 9409728 9f025df 9409728 |
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 |
---
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 |