Update README.md

README.md

@@ -21,61 +21,112 @@ task_categories:
 
 ## Dataset Overview
 
-PolarFree is a high-quality dataset designed for polarization-based reflection removal tasks, as introduced in the CVPR 2025 paper "PolarFree: Polarization-based Reflection-Free Imaging". The dataset aims to support tasks such as image reflection removal and image enhancement, particularly suitable for training and evaluating image enhancement models.
+PolarFree is a high-quality dataset designed for polarization-based reflection removal tasks, as introduced in the CVPR 2025 paper "PolarFree: Polarization-based Reflection-Free Imaging". The dataset aims to support tasks such as image reflection removal and image enhancement, particularly suitable for training and evaluating polarization-based image reflection removal models.
+
+## Download Dataset
+```
+huggingface-cli download Mingde/PolaRGB --repo-type dataset --local-dir ./PolaRGB
+```
 
 ## Dataset Structure
 
-The dataset is organized as follows:
+The dataset is organized as follows:
 
 ```
 dataset/
 ├── train/
-│   └── scene_id/
-│       ├── input/
-│       │   ├── 000_000.png
-│       │   ├── 000_045.png
-│       │   └── ...
-│       └── gt/
-│           ├── 000_000.png
-│           ├── 000_045.png
-│           └── ...
+│   ├── easy (or hard)/                     # difficulty split
+│   │   ├── input/
+│   │   │   ├── 00/                         # scene 0
+│   │   │   │   ├── 000_000.png
+│   │   │   │   ├── 000_045.png
+│   │   │   │   ├── 000_090.png
+│   │   │   │   ├── 000_135.png
+│   │   │   │   ├── 000_rgb.png
+│   │   │   │   ├── 001_000.png
+│   │   │   │   ├── 001_045.png
+│   │   │   │   ├── 001_090.png
+│   │   │   │   ├── 001_135.png
+│   │   │   │   ├── 001_rgb.png
+│   │   │   │   └── ...
+│   │   │   ├── 01/                         # scene 1
+│   │   │   │   ├── 000_000.png
+│   │   │   │   ├── 000_045.png
+│   │   │   │   ├── 000_090.png
+│   │   │   │   ├── 000_135.png
+│   │   │   │   ├── 000_rgb.png
+│   │   │   │   ├── 001_000.png
+│   │   │   │   ├── 001_045.png
+│   │   │   │   ├── 001_090.png
+│   │   │   │   ├── 001_135.png
+│   │   │   │   ├── 001_rgb.png
+│   │   │   │   └── ...
+│   │   │   └── ...
+│   │   ├── gt/
+│   │   │   ├── 00/                         # scene 0
+│   │   │   │   ├── 000_000.png
+│   │   │   │   ├── 000_045.png
+│   │   │   │   ├── 000_090.png
+│   │   │   │   ├── 000_135.png
+│   │   │   │   └── 000_rgb.png
+│   │   │   ├── 01/                         # scene 1
+│   │   │   │   ├── 000_000.png
+│   │   │   │   ├── 000_045.png
+│   │   │   │   ├── 000_090.png
+│   │   │   │   ├── 000_135.png
+│   │   │   │   └── 000_rgb.png
+│   │   │   └── ...
+│
 ├── test/
-│   └── scene_id/
-│       ├── input/
-│       │   ├── 000_000.png
-│       │   ├── 000_045.png
-│       │   └── ...
-│       └── gt/
-│           ├── 000_000.png
-│           ├── 000_045.png
-│           └── ...
+│   ├── input/
+│   │   ├── 00/                             # scene 0
+│   │   │   ├── 000_000.png
+│   │   │   ├── 000_045.png
+│   │   │   ├── 000_090.png
+│   │   │   ├── 000_135.png
+│   │   │   ├── 000_rgb.png
+│   │   │   └── ...
+│   │   ├── 01/                             # scene 1
+│   │   │   ├── 000_000.png
+│   │   │   ├── 000_045.png
+│   │   │   ├── 000_090.png
+│   │   │   ├── 000_135.png
+│   │   │   ├── 000_rgb.png
+│   │   │   └── ...
+│   │   └── ...
+│
+│   ├── gt/
+│   │   ├── 00/                             # scene 0
+│   │   │   ├── 000_000.png
+│   │   │   ├── 000_045.png
+│   │   │   ├── 000_090.png
+│   │   │   ├── 000_135.png
+│   │   │   └── 000_rgb.png
+│   │   ├── 01/                             # scene 1
+│   │   │   ├── 000_000.png
+│   │   │   ├── 000_045.png
+│   │   │   ├── 000_090.png
+│   │   │   ├── 000_135.png
+│   │   │   └── 000_rgb.png
+│   │   └── ...
+└── ...
 ```
 
-- **input/scene_id/**: Contains multiple input images captured at different polarization angles. Each group of images shares the same prefix number (e.g., 000, 001), indicating they belong to the same set.
-- **gt/scene_id/**: Contains the corresponding high-quality ground truth images used as references for the input images.
-
-```json
-{
-  "inputs": [
-    "input/scene_id/001_000.png",
-    "input/scene_id/001_045.png",
-    "input/scene_id/001_090.png",
-    "input/scene_id/001_rgb.png"
-  ],
-  "gt": [
-    "gt/scene_id/000_000.png",
-    "gt/scene_id/000_045.png",
-    "gt/scene_id/000_090.png",
-    "gt/scene_id/000_rgb.png"
-  ]
-}
-```
+1. The dataset is divided into **train** and **test** subsets, and both follow a similar directory structure.
+2. The **train** subset is further divided into **easy** and **hard** sets, which share the same internal structure. The **test** subset is not split by difficulty, but its structure is identical.
+3. Taking the **test** set as an example, it contains two subfolders: **input** and **gt**. The *input* folder stores images with reflections, while the *gt* folder contains the corresponding clean images without reflections. Both folders include the same number of scenes (e.g., 00, 01, 02, ...).
+4. In `test/input/00`, there are multiple images named in the format `xxx_yyy.png`. Here, **xxx** denotes the index of the captured sample within scene `00`. **yyy** may be one of {000, 045, 090, 135, rgb}: the first four represent polarization-based images, and `rgb` corresponds to the RGB image of the current scene.
+5. In `test/gt/00`, there is a single image named `000_yyy.png`, where '000_rgb.png' serves as the ground truth for all captured samples in the corresponding `input/00` folder.
+
+To train or evaluate a polarization-based reflection removal model, each sample pair can be constructed as follows. For a given scene (e.g., 00), the input consists of five images—000_000.png, 000_045.png, 000_090.png, 000_135.png, and 000_rgb.png—and the corresponding ground truth is gt/00/000_rgb.png. Similarly:
+
+- input/00/{001_000.png, 001_045.png, 001_090.png, 001_135.png, 001_rgb.png} → gt/00/000_rgb.png
 
-The training and testing data are all available! If you want raw images, please contact me via mingdeyao@foxmail.com.
+- input/00/{002_000.png, 002_045.png, 002_090.png, 002_135.png, 002_rgb.png} → gt/00/000_rgb.png
 
-## Supported Task
+and so on for the remaining examples within the same scene.
 
-- **Image Reflection Removal**: Utilizing polarization information to remove reflections from input images, resulting in clearer images.
+If you want raw images, please find them at https://huggingface.co/datasets/Mingde/PolaRGB_raw or contact me via mingdeyao@foxmail.com.
 
 ## Citation