README.md

---
license: apache-2.0
image:
   underwater laser imaging
---

# 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
```