NITRDrone-Dataset

KO | EN

gitlite — search

#ai #typescript #go #android #machine-learning #deep-learning #docker #java #windows #awesome #cli #vue #security #pytorch

NITRDrone-Dataset

(★ 14)

This is an aerial image dataset for semantic scene understanding.

NITRDrone-Dataset Latest Version Download

Download Latest Version (.zip)

// repository documentation

Was this content helpful?

★ 0 (0 ratings)

<p align="center">
 <img src="https://github.com/drone-vision/NITRDrone-Dataset/blob/main/readme_images/frame271-ok.jpg" width=150 height=150 alt="centered logo" />
 </p>
<h1 align="center">NITRDrone Dataset (NITRDD)</h1>

This is an aerial image dataset for semantic scene understanding and is under development.

## LOG
|Date   | Log  |
|---|---|
| 2019.09.01  | Initialization  |
| 2021.09.23  |  NITRDD(4) released |

## Dataset Overview:
-NITRDD
| class  | GT  | (R, G, B)  |
|---|---|---|
| _background_ | 0   | (0, 0, 0)  |
| _road_ |  1 |  (128, 0, 0) |
| _occluded_road_ |  2 | (0, 128, 0)  |
| _vegetation_ |  3 | (128, 128, 0)  |
## Directory Structure:
```
NITRDrone Dataset
│
└─── readme_images
|
└─────────data
│          |
│          └─── train
|          |       └───| images 
|          |       └───| gray_masks
|          |       └───| rgb_masks
|          └───   val
|          |       └───| images 
|          |       └───| gray_masks
|          |       └───| rgb_masks
|          |        
|          |    .gitignore
|          | 
|          |     frame271.jpg
|          ...
└───utils
│   │  label_generator.py
│   │  labels.txt 
│   │  requirements.txt
│   ...
│   
|   .gitignore
|    CITATION.cff
|    LICENSE
|    README.md
|   ...
```

DESCRIPTION:<br />
|Folder Name| Description |
|---|---|
| train| contains three folders as images, rgb_masks, gray_masks|
| val| contains three folders as images, rgb_masks, gray_masks|
| images  | Aerial images captured by DJI Phantom 4 drone  |
| rgb_masks | RGB masks of the corresponding images generated after annotations  |
|  gray_masks    | Gray scale masks of the corresponding images     |
| utils  | Important files related to dataset preparation  |

## Benchmark
The benchmark is released to look for better solutions for the proposed dataset **(NITRDD)**. The performance metrics that are used OA (Overall Accuracy/pixelwise accuracy), mIoU (mean Intersection over Union).
Researchers are welcomed to contribute new results!

-Obtained Results (NITRDD(4))
| Models  | #Parameters  | OA | mIoU |
|---------|--------------|----|------|
|FCN-8s   |   136*M*           |  0.72  |  0.16     |
|FCN-16s   |  134*M*            | 0.83   | 0.68     |
|FCN-32s   |  134*M*            | 0.86   | 0.63     |
|FC_Densenet_103   |  9.42*M* | 0.91   | 0.62     |
|E-Net   |     350.65*K*         | 0.89   | 0.65    |
|LinkNet   |   1.15*M*           | 0.93  |  0.46    |

## Sample Images
<table>
     
  <tr>
    <td>image</td>
     <td>mask</td>
  </tr>
  <tr>
    <td><img src="https://github.com/drone-vision/NITRDrone-Dataset/blob/main/readme_images/imgs/NITR_AC_JAN26_30.jpg" width=480 height=270></td>
    <td><img src="https://github.com/drone-vision/NITRDrone-Dataset/blob/main/readme_images/seg_class/NITR_AC_JAN26_30.png" width=480 height=270></td>
  </tr>
  <tr>
    <td><img src="https://github.com/drone-vision/NITRDrone-Dataset/blob/main/readme_images/imgs/NITR_FR_1.jpg" width=480 height=270></td>
    <td><img src="https://github.com/drone-vision/NITRDrone-Dataset/blob/main/readme_images/seg_class/NITR_FR_1.png" width=480 height=270></td>
  </tr>
  <tr>
    <td><img src="https://github.com/drone-vision/NITRDrone-Dataset/blob/main/readme_images/imgs/NITR_FR_6.jpg" width=480 height=270></td>
    <td><img src="https://github.com/drone-vision/NITRDrone-Dataset/blob/main/readme_images/seg_class/NITR_FR_6.png" width=480 height=270></td>
  </tr>
 </table>

## Download Link:
- NITRDrone(4): (train+val) <br />
[GDrive](https://drive.google.com/drive/folders/1IQUadXFpEFEsB_9I5JVUuGJBjqIL5MFG?usp=sharing)

## LICENSE:

This dataset is licenensed to Visual Surveillance Laboratory, Department of Computer Science and Engineering, National Institute of Technology, Rourkela, India.

## Citation & Acknowledgements

This dataset is available publicly for only for non-commercial use. If you use this dataset in your research or wish to refer to the baseline results published    in the README, please cite the work from Cite this repository as:

@article{nitrdd2021,
        title={The NITRDrone Dataset to Address the Challenges for Road Extraction from Aerial Images},
        author={Behera, Tanmay Kumar and Bakshi, Sambit and Sa, Pankaj Kumar and Nappi, Michael and Castiglione, Aniello and Vijayakumar, Pandi   and Gupta, Brij},        
        journal = {Journal of Signal Processing Systems},
        publisher={Springer},
        year={2021}, 
        note = "doi:10.1007/s11265-022-01777-0"
     }

NITRDrone-Dataset

NITRDrone-Dataset Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

NITRDrone-Dataset

NITRDrone-Dataset Latest Version Download

Today's picks

Was this content helpful?

Recent Feedback

Download README