| --- |
| license: mit |
| language: |
| - en |
| --- |
| |
| <div align="center"> |
| |
| # SkyScenes: A Synthetic Dataset for Aerial Scene Understanding |
| [Sahil Khose](https://sahilkhose.github.io/)\*, [Anisha Pal](https://anipal.github.io/)\*, [Aayushi Agarwal](https://www.linkedin.com/in/aayushiag/)\*, [Deepanshi](https://www.linkedin.com/in/deepanshi-d/)\*, [Judy Hoffman](https://faculty.cc.gatech.edu/~judy/), [Prithvijit Chattopadhyay](https://prithv1.xyz/) |
| </div> |
|
|
| <!-- This repository is the official Pytorch implementation for [SkyScenes](). --> |
|
|
| [](https://huggingface.co/datasets/hoffman-lab/SkyScenes) [](https://github.gatech.edu/pages/hoffman-group/SkyScenes/) []() |
|
|
|
|
| <!-- [](./assets/robust_aerial_videos.mp4) --> |
|
|
| <img src="./assets/skyscene_intro_teaser.png" width="100%"/> |
|
|
| ## Dataset Summary |
|
|
| Real-world aerial scene understanding is limited by a lack of datasets that contain densely annotated images curated under a diverse set of conditions. |
| Due to inherent challenges in obtaining such images in controlled real-world settings, |
| we present SkyScenes, a synthetic dataset of densely annotated aerial images captured from Unmanned Aerial Vehicle (UAV) perspectives. |
| **SkyScenes** images are carefully curated from **CARLA** to comprehensively capture diversity across layout (urban and rural maps), weather conditions, times of day, pitch angles and altitudes with corresponding semantic, instance and depth annotations. |
| **SkyScenes** features **33,600** images in total, which are spread across 8 towns, 5 weather and daytime conditions and 12 height and pitch variations. |
|
|
|
|
| <details> |
| <summary>Click to view the detailed list of all variations</summary> |
| |
| - **Layout Variations(Total 8):**: |
| - Town01 |
| - Town02 |
| - Town03 |
| - Town04 |
| - Town05 |
| - Town06 |
| - Town07 |
| - Town10HD |
| _Town07 features Rural Scenes, whereas the rest of the towns feature Urban scenes_ |
|
|
| - **Weather & Daytime Variations(Total 5):** |
| - ClearNoon |
| - ClearSunset |
| - ClearNight |
| - CloudyNoon |
| - MidRainyNoon |
|
|
| - **Height and Pitch Variations of UAV Flight(Total 12):** |
| - Height = 15m, Pitch = 0° |
| - Height = 15m, Pitch = 45° |
| - Height = 15m, Pitch = 60° |
| - Height = 15m, Pitch = 90° |
| - Height = 35m, Pitch = 0° |
| - Height = 35m, Pitch = 45° |
| - Height = 35m, Pitch = 60° |
| - Height = 35m, Pitch = 90° |
| - Height = 60m, Pitch = 0° |
| - Height = 60m, Pitch = 45° |
| - Height = 60m, Pitch = 60° |
| - Height = 60m, Pitch = 90° |
| </details> |
| <details> |
| <summary>Click to view class definitions, color palette and class IDs for Semantic Segmentation</summary> |
|
|
| **SkyScenes** semantic segmentation labels span 28 classes which can be further collapsed to 20 classes. |
| | Class ID | Class ID (collapsed) | RGB Color Palette | Class Name | Definition | |
| |----------|--------------------|-------------------|------------------|----------------------------------------------------------------------------------------------------| |
| | 0 | -1 | <span style="color:rgb(0, 0, 0)"> (0, 0, 0) </span> | unlabeled | Elements/objects in the scene that have not been categorized | |
| | 1 | 2 | <span style="color:rgb(70, 70, 70)"> (70, 70, 70) </span> | building | Includes houses, skyscrapers, and the elements attached to them | |
| | 2 | 4 | <span style="color:rgb(190, 153, 153)"> (190, 153, 153) </span> | fence | Wood or wire assemblies that enclose an area of ground | |
| | 3 | -1 | <span style="color:rgb(55, 90, 80)"> (55, 90, 80) </span> | other | Uncategorized elements | |
| | 4 | 11 | <span style="color:rgb(220, 20, 60)"> (220, 20, 60) </span> | pedestrian | Humans that walk | |
| | 5 | 5 | <span style="color:rgb(153, 153, 153)"> (153, 153, 153) </span> | pole | Vertically oriented pole and its horizontal components if any | |
| | 6 | 16 | <span style="color:rgb(157, 234, 50)"> (157, 234, 50) </span> | roadline | Markings on road | |
| | 7 | 0 | <span style="color:rgb(128, 64, 128)"> (128, 64, 128) </span> | road | Lanes, streets, paved areas on which cars drive | |
| | 8 | 1 | <span style="color:rgb(244, 35, 232)"> (244, 35, 232) </span> | sidewalk | Parts of ground designated for pedestrians or cyclists | |
| | 9 | 8 | <span style="color:rgb(107, 142, 35)"> (107, 142, 35) </span> | vegetation | Trees, hedges, all kinds of vertical vegetation (ground-level vegetation is not included here) | |
| | 10 | 13 | <span style="color:rgb(0, 0, 142)"> (0, 0, 142) </span> | cars | Cars in scene | |
| | 11 | 3 | <span style="color:rgb(102, 102, 156)"> (102, 102, 156) </span> | wall | Individual standing walls, not part of buildings | |
| | 12 | 7 | <span style="color:rgb(220, 220, 0)"> (220, 220, 0) </span> | traffic sign | Signs installed by the state/city authority, usually for traffic regulation | |
| | 13 | 10 | <span style="color:rgb(70, 130, 180)"> (70, 130, 180) </span> | sky | Open sky, including clouds and sun | |
| | 14 | -1 | <span style="color:rgb(81, 0, 81)"> (81, 0, 81) </span> | ground | Any horizontal ground-level structures that do not match any other category | |
| | 15 | -1 | <span style="color:rgb(150, 100, 100)"> (150, 100, 100) </span> | bridge | The structure of the bridge | |
| | 16 | -1 | <span style="color:rgb(230, 150, 140)"> (230, 150, 140) </span> | railtrack | Rail tracks that are non-drivable by cars | |
| | 17 | -1 | <span style="color:rgb(180, 165, 180)"> (180, 165, 180) </span> | guardrail | Guard rails / crash barriers | |
| | 18 | 6 | <span style="color:rgb(250, 170, 30)"> (250, 170, 30) </span> | traffic light | Traffic light boxes without their poles | |
| | 19 | -1 | <span style="color:rgb(110, 190, 160)"> (110, 190, 160) </span> | static | Elements in the scene and props that are immovable | |
| | 20 | -1 | <span style="color:rgb(170, 120, 50)"> (170, 120, 50) </span> | dynamic | Elements whose position is susceptible to change over time | |
| | 21 | 19 | <span style="color:rgb(45, 60, 150)"> (45, 60, 150) </span> | water | Horizontal water surfaces | |
| | 22 | 9 | <span style="color:rgb(152, 251, 152)"> (152, 251, 152) </span> | terrain | Grass, ground-level vegetation, soil, or sand | |
| | 23 | 12 | <span style="color:rgb(255, 0, 0)"> (255, 0, 0) </span> | rider | Humans that ride/drive any kind of vehicle or mobility system | |
| | 24 | 18 | <span style="color:rgb(119, 11, 32)"> (119, 11, 32) </span> | bicycle | Bicycles in scenes | |
| | 25 | 17 | <span style="color:rgb(0, 0, 230)"> (0, 0, 230) </span> | motorcycle | Motorcycles in scene | |
| | 26 | 15 | <span style="color:rgb(0, 60, 100)"> (0, 60, 100) </span> | bus | Buses in scenes | |
| | 27 | 14 | <span style="color:rgb(0, 0, 70)"> (0, 0, 70) </span> | truck | Trucks in scenes | |
| | |
| </details> |
| |
| ## Dataset Structure |
|
|
| The dataset is organized in the following structure: |
| <!--<details> |
| <summary><strong>Images (RGB Images)</strong></summary> |
|
|
| - ***H_15_P_0*** |
| - *ClearNoon* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| - *ClearSunset* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| - *ClearNight* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| - *CloudyNoon* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| - *MidRainyNoon* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| - ***H_15_P_45*** |
| - ... |
| - ... |
| - ***H_60_P_90*** |
| - ... |
| </details> |
|
|
| <details> |
| <summary><strong>Instance (Instance Segmentation Annotations)</strong></summary> |
|
|
| - ***H_35_P_45*** |
| - *ClearNoon* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| </details> |
|
|
| <details> |
| <summary><strong>Segment (Semantic Segmentation Annotations)</strong></summary> |
|
|
| - ***H_15_P_0*** |
| - *ClearNoon* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| - ***H_15_P_45*** |
| - ... |
| - ... |
| - ***H_60_P_90*** |
| </details> |
|
|
| <details> |
| <summary><strong>Depth (Depth Annotations)</strong></summary> |
|
|
| - ***H_35_P_45*** |
| - *ClearNoon* |
| - Town01.tar.gz |
| - Town02.tar.gz |
| - ... |
| - Town10HD.tar.gz |
| </details> |
| --> |
|
|
|
|
| ``` |
| ├── Images (RGB Images) |
| │ ├── H_15_P_0 |
| │ │ ├── ClearNoon |
| │ │ │ ├── Town01 |
| │ │ │ │ └── Town01.tar.gz |
| │ │ │ ├── Town02 |
| │ │ │ │ └── Town02.tar.gz |
| │ │ │ ├── ... |
| │ │ │ └── Town10HD |
| │ │ │ └── Town10HD.tar.gz |
| │ │ ├── ClearSunset |
| │ │ │ ├── Town01 |
| │ │ │ │ └── Town01.tar.gz |
| │ │ │ ├── Town02 |
| │ │ │ │ └── Town02.tar.gz |
| │ │ │ ├── ... |
| │ │ │ └── Town10HD |
| │ │ │ └── Town10HD.tar.gz |
| │ │ ├── ClearNight |
| │ │ │ ├── Town01 |
| │ │ │ │ └── Town01.tar.gz |
| │ │ │ ├── Town02 |
| │ │ │ │ └── Town02.tar.gz |
| │ │ │ ├── ... |
| │ │ │ └── Town10HD |
| │ │ │ └── Town10HD.tar.gz |
| │ │ ├── CloudyNoon |
| │ │ │ ├── Town01 |
| │ │ │ │ └── Town01.tar.gz |
| │ │ │ ├── Town02 |
| │ │ │ │ └── Town02.tar.gz |
| │ │ │ ├── ... |
| │ │ │ └── Town10HD |
| │ │ │ └── Town10HD.tar.gz |
| │ │ └── MidRainyNoon |
| │ │ ├── Town01 |
| │ │ │ └── Town01.tar.gz |
| │ │ ├── Town02 |
| │ │ │ └── Town02.tar.gz |
| │ │ ├── ... |
| │ │ └── Town10HD |
| │ │ └── Town10HD.tar.gz |
| │ ├── H_15_P_45 |
| │ │ └── ... |
| │ ├── ... |
| │ └── H_60_P_90 |
| │ └── ... |
| ├── Instance (Instance Segmentation Annotations) |
| │ ├── H_35_P_45 |
| │ │ └── ClearNoon |
| │ │ ├── Town01 |
| │ │ │ └── Town01.tar.gz |
| │ │ ├── Town02 |
| │ │ │ └── Town02.tar.gz |
| │ │ ├── ... |
| │ │ └── Town10HD |
| │ │ └── Town10HD.tar.gz |
| │ └── ... |
| ├── Segment (Semantic Segmentation Annotations) |
| │ ├── H_15_P_0 |
| │ │ ├── ClearNoon |
| │ │ │ ├── Town01 |
| │ │ │ │ └── Town01.tar.gz |
| │ │ │ ├── Town02 |
| │ │ │ │ └── Town02.tar.gz |
| │ │ │ ├── ... |
| │ │ │ └── Town10HD |
| │ │ │ └── Town10HD.tar.gz |
| │ │ ├── H_15_P_45 |
| │ │ │ └── ... |
| │ │ ├── ... |
| │ │ └── H_60_P_90 |
| │ │ └── ... |
| │ └── ... |
| └── Depth (Depth Annotations) |
| ├── H_35_P_45 |
| │ └── ClearNoon |
| │ ├── Town01 |
| │ │ └── Town01.tar.gz |
| │ ├── Town02 |
| │ │ └── Town02.tar.gz |
| │ ├── ... |
| │ └── Town10HD |
| │ └── Town10HD.tar.gz |
| └── ... |
| |
| ``` |
| |
| **Note**: Since the same viewpoint is reproduced across each weather variation, hence ClearNoon annotations can be used for all images pertaining to the different weather variations. |
| |
| ## Dataset Download |
|
|
|
|
|
|
| The dataset can be downloaded using both [datasets](https://huggingface.co/docs/datasets/index) library by Hugging Face and wget. Since SkyScenes offers variations across different axes |
| hence we enable different subsets for download that can aid in model sensitivity analysis across these axes. |
|
|
|
|
| **Example script for downloading different subsets of data using wget** |
| ``` |
| #!/bin/bash |
| #Change here to download a specific Height and Pitch Variation, for example - H_15_P_0 |
| HP=('H_15_P_0' 'H_15_P_45' 'H_15_P_60' 'H_15_P_90' 'H_35_P_0' 'H_35_P_45' 'H_35_P_60' 'H_35_P_90' 'H_60_P_0' 'H_60_P_45' 'H_60_P_60' 'H_60_P_90') |
| |
| #Change here to download a specific weather subset, for example - ClearNoon |
| weather=('ClearNoon' 'ClearNight' 'ClearSunset' 'CloudyNoon' 'MidRainyNoon') |
| |
| #Change here to download a specific Town subset, for example - Town07 |
| layout=('Town01' 'Town02' 'Town03' 'Town04' 'Town05' 'Town06' 'Town07' 'Town10HD') |
| |
| #Change here for any specific annotation, for example - https://huggingface.co/datasets/hoffman-lab/SkyScenes/resolve/main/Segment |
| base_url=('https://huggingface.co/datasets/hoffman-lab/SkyScenes/resolve/main/Images' 'https://huggingface.co/datasets/hoffman-lab/SkyScenes/resolve/main/Segment' 'https://huggingface.co/datasets/hoffman-lab/SkyScenes/resolve/main/Instance''https://huggingface.co/datasets/hoffman-lab/SkyScenes/resolve/main/Depth') |
| |
| #Change here for base download folder |
| base_download_folder='SkyScenes' |
| |
| |
| for hp in "${HP[@]}"; do |
| for w in "${weather[@]}"; do |
| for t in "${layout[@]}"; do |
| for url in "${base_url[@]}"; do |
| folder=$(echo "$url" | awk -F '/' '{print $(NF)}') |
| download_url="${url}/${hp}/${w}/${t}/${t}.tar.gz" |
| download_folder="${base_download_folder}/${folder}/${HP}/${w}/${t}" |
| mkdir -p "$download_folder" |
| echo "Downloading: $download_url" |
| echo "SAving: $download_folder" |
| # wget -P "$download_folder" "$download_url" |
| done |
| done |
| done |
| done |
| ``` |
|
|
| ### 💡 Support for [datasets](https://huggingface.co/docs/datasets/index) will be made available soon ! |
