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README.md

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+# Cityscapes VPS
+
+This dataset is derived from the videos in the *validation* split of the Cityscapes[^1] dataset.
+It aggregates the images and metadata from Cityscapes[^1], Cityscapes-VPS[^2] and Cityscapes-DVPS[^3] into a single structured format. 
+This comprehensive derivative was created out of the need for a batteries-included variant of the dataset for academic purposes.
+Specifically, joining samples from the individual datasets in their original structure (each is organized differently) involves a significant amount of boilerplate code. 
+
+[^1]: `Cordts et al., “The Cityscapes Dataset for Semantic Urban Scene Understanding” (CVPR 2016)`
+
+[^2]: `Kim et al., "Video Panoptic Segmentation" (CVPR 2020)`
+
+[^3]: `Qiao et al., "Learning Visual Perception with Depth-aware Video Panoptic Segmentation" (CVPR 2021)`
+
+
+This dataset is relevant to computer vision research areas such as:
+
+- Segmentation
+- Depth estimation
+- Autonomous driving
+- Video understanding
+
+## Overview
+The following variables are included.
+
+1. **Images.** The input data captured by the left camera from Cityscapes[^1], in 8-bit format. Every sequence has 30 frames.
+2. **Segmentation labels.** Derived from Cityscapes[^1] and Cityscapes-DVPS[^3], these labels provide detailed semantic segmentation and instance segmentation information for 6 frames of every sequence.
+3. **Depth maps.** Improved depth information from Cityscapes-DVPS[^3], offering enhanced quality over the disparity package from Cityscapes[^1], provided for the same samples as the segmentation labels above.
+4. **Camera calibrations.** Includes the intrinsic and extrinsic parameters provided by Cityscapes[^1] for each sequence.
+5. **Vehicle odometry.** Odometry data for each frame, a subset of those provided in Cityscapes[^1].
+
+Files are grouped by split, sequence and frame.
+This leads to the following structure:
+```text
+data
+    train
+        000000
+            000000.image.png
+            000000.panoptic.png
+            000000.depth.png
+            000000.vehicle.json
+            000000.timestamp.txt
+            000000.camera.json
+            000001.image.png
+            000001.panoptic.png
+            000001.depth.png
+            000001.vehicle.json
+            000001.timestamp.txt
+            000001.camera.json
+            ...
+        000001
+            ...
+    val
+        000000
+            ...
+        000001
+            ....
+    test
+        000000
+            ...
+        000001
+            ....
+
+```
+
+The `data` directory in this repository only contains the segmentation and depth map annotations.
+The remaining data should be downloaded from official sources using the provided preparation script.
+
+
+## Preparation
+
+1. Install the [Cityscapes developer kit](https://github.com/mcordts/cityscapesScripts) using `pip`.
+
+```bash
+python -m pip install cityscapesscripts
+```
+
+2. Run the preparation script provided in this repository. 
+   Note that this may prompt your [Cityscapes account](https://cityscapes-dataset.com/login/) login credentials.
+
+```bash
+python scripts/download.py downloads data manifest.csv
+```
+
+3. Remove the downloaded Cityscapes archive files to save disk space (optional).
+
+```bash
+rm -r downloads
+```
+
+
+## License
+
+Please refer to the Cityscapes license for more details.
+
+
+## Citation
+
+If you use this dataset in your research, please cite the original 
+[Cityscapes](https://cityscapes-dataset.com), 
+[Cityscapes-VPS](https://github.com/mcahny/vps), and
+[Cityscapes-DVPS](https://github.com/joe-siyuan-qiao/ViP-DeepLab) datasets.
+
+