StreakNet-Dataset

# StreakNet-Dataset

**StreakNet-Dataset** is an underwater laser imaging dataset for **UCLR** systems. It comprises a collection of streak-tube images captured by a **UCLR** system at distances of 10m, 13m, 15m, and 20m. See the table below to learn more details of the dataset.

|Distance|Number of streak-tube images|Resolution of streak-tube images|Data type|Training set|Validation set|Test set|
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
|10m|400|2048x2048|uint16|315,200|40,800|819,200|
|13m|349|2048x2048|uint16|281,992|47,530|714,752|
|15m|300|2048x2048|uint16|245,400|39,200|614,400|
|20m|267|2048x2048|uint16|229,086|31,240|546,816|

### Download

You can download **StreakNet-Dataset** for free from [HuggingFace](https://huggingface.co/datasets/Coder-AN/StreakNet-Dataset) or [ModelScope](https://modelscope.cn/datasets/CoderAN/StreakNet-Dataset/) by Git.

Firstly, install `git-lfs`.

```sh
curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
sudo apt update
sudo apt install git-lfs
sudo git lfs install --system
```

Then, download **StreakNet-Dataset** in work directory of StreakNet.

* From [HuggingFace](https://huggingface.co/datasets/Coder-AN/StreakNet-Dataset): For Global Users

```sh
cd StreakNet
git clone https://huggingface.co/datasets/Coder-AN/StreakNet-Dataset ./datasets
```

* From [ModelScope](https://modelscope.cn/datasets/CoderAN/StreakNet-Dataset): For Chinese Users

```sh
cd StreakNet
git clone https://www.modelscope.cn/datasets/CoderAN/StreakNet-Dataset.git ./datasets
```

### Organizational Structure

After downloading **StreakNet-Dataset** from [HuggingFace](https://huggingface.co/datasets/Coder-AN/StreakNet-Dataset) or [ModelScope](https://modelscope.cn/datasets/CoderAN/StreakNet-Dataset/), you will see the following directory structure.

```sh
datasets
|- clean_water_10m # The directory of data taken at a distance of 10m
| |- data # Original streak images
| | |- 001.tif
| | |- 002.tif
| | |- 003.tif
| | |- ...
| |
| |- groundtruth.npy # The ground-truth of the final imaged image
| |- preview.jpg # A preview of the ground-truth
|
|- clean_water_13m # The directory of data taken at a distance of 13m (has the same structure as 10m)
|- clean_water_15m # The directory of data taken at a distance of 15m (has the same structure as 10m)
|- clean_water_20m # The directory of data taken at a distance of 20m (has the same structure as 10m)
|- template.npy # The 1-D time sequence of the template signal
|- test_config.yaml # The config file of test-set
|- train_config.yaml # The config file of training-set
|- valid_config.yaml # The config file of validation-set
```

# StreakNet数据集

**StreakNet数据集**是一款面向**UCLR系统**（UCLR）的水下激光成像数据集，收录了由UCLR系统在10米、13米、15米及20米测距条件下采集的条纹管图像集合。详情可参阅下表：

| 测距 | 条纹管图像数量 | 条纹管图像分辨率 | 数据类型 | 训练集 | 验证集 | 测试集 |
|:---:|:---:|:---:|:---:|:---:|:---:|:---:|
| 10m | 400 | 2048x2048 | uint16 | 315,200 | 40,800 | 819,200 |
| 13m | 349 | 2048x2048 | uint16 | 281,992 | 47,530 | 714,752 |
| 15m | 300 | 2048x2048 | uint16 | 245,400 | 39,200 | 614,400 |
| 20m | 267 | 2048x2048 | uint16 | 229,086 | 31,240 | 546,816 |

### 下载方式

用户可通过Git工具免费从[HuggingFace](https://huggingface.co/datasets/Coder-AN/StreakNet-Dataset)或[ModelScope](https://modelscope.cn/datasets/CoderAN/StreakNet-Dataset/)下载StreakNet数据集。

首先安装`git-lfs`：
sh
curl -s https://packagecloud.io/install/repositories/github/git-lfs/script.deb.sh | sudo bash
sudo apt update
sudo apt install git-lfs
sudo git lfs install --system

随后在StreakNet项目的工作目录中下载StreakNet数据集：

* 面向全球用户：从[HuggingFace](https://huggingface.co/datasets/Coder-AN/StreakNet-Dataset)下载
sh
cd StreakNet
git clone https://huggingface.co/datasets/Coder-AN/StreakNet-Dataset ./datasets

* 面向中国用户：从[ModelScope](https://modelscope.cn/datasets/CoderAN/StreakNet-Dataset)下载
sh
cd StreakNet
git clone https://www.modelscope.cn/datasets/CoderAN/StreakNet-Dataset.git ./datasets

### 数据集目录结构

从上述平台下载StreakNet数据集后，将得到如下目录结构：
sh
datasets
|- clean_water_10m # 10米测距下的采集数据目录
| |- data # 原始条纹图像
| | |- 001.tif
| | |- 002.tif
| | |- 003.tif
| | |- ...
| |
| |- groundtruth.npy # 最终成像结果的真值数据
| |- preview.jpg # 真值结果预览图
|
|- clean_water_13m # 13米测距下的采集数据目录（目录结构与10米组一致）
|- clean_water_15m # 15米测距下的采集数据目录（目录结构与10米组一致）
|- clean_water_20m # 20米测距下的采集数据目录（目录结构与10米组一致）
|- template.npy # 模板信号的一维时序数据
|- test_config.yaml # 测试集配置文件
|- train_config.yaml # 训练集配置文件
|- valid_config.yaml # 验证集配置文件