Update README.md

README.md

@@ -1,3 +1,134 @@
----
-license: apache-2.0
----
+# IITKGP_Fence dataset
+
+## Overview
+The **IITKGP_Fence dataset** is designed for tasks related to fence-like occlusion detection, defocus blur, depth mapping, and object segmentation. The captured data vaies in scene composition, background defocus, and object occlusions. 
+The dataset comprises both labeled and unlabeled data, as well as additional video and RGB-D data. The contains ground truth occlusion masks (`GT`) for the corresponding images. We created the ground truth occlusion labels in a semi-automatic way with user interaction.
+
+
+## Dataset Structure
+<details>
+<summary>Click to expand directory structure</summary>
+
+<pre style="font-size: 12px;">
+└───IITKGP_Fence dataset
+    ├───Labeled
+    │   ├───GT
+    │   │       (1).png
+    │   │       ...
+    │   │       (175).png
+    │   │       
+    │   ├───Imgs
+    │   │       (1).png
+    │   │       ...
+    │   │       (175).png
+    │   │       
+    │   └───Others
+    │       ├───Bird
+    │       │       c1.png
+    │       │       ...
+    │       │       f1.png
+    │       │       
+    │       ├───Blurred_bg
+    │       │   ├───GT
+    │       │   │       gt1.jpg
+    │       │   │       ...
+    │       │   │       gt88.jpg
+    │       │   │              
+    │       │   └───Imgs
+    │       │       im (1).jpg
+    │       │       ...
+    │       │       im (88).jpg
+    │       │                      
+    │       └───...
+    └───Unlabeled
+        ├───DefocusBlurred
+        │   └───Blurred_fg
+        │       │   BlMov_01.mov
+        │       │   ...
+        │       │   BlMov_46.mov
+        │       │   
+        │       └───Imgs
+        │               BlJPG_01.jpg
+        │               ...
+        ├───RGB
+        │   ├───Imgs
+        │   │       BlJPG_001.jpg
+        │   │       ...
+        │   │       BlJPG_205.jpg
+        │   │       
+        │   └───Vids
+        │       ├───utils
+        │       └───Zoo
+        │               Zoo_001.mp4
+        │               ...
+        │               Zoo_205.mp4
+        └───RGBD
+            │   data1.mat
+            │   ...   
+            ├───Othersamples
+            │   ├───DATA1
+            │   └───...
+            └───utils
+</pre>
+
+</details>
+
+### Dataset Description
+ Here's an overview of its structure and contents:
+
+1. **Labeled Data**:
+   - **GT (Ground Truth)**: Contains 175 PNG images representing the ground truth labels for corresponding input images.
+   - **Imgs**: Contains 175 PNG images, which are RGB images that correspond to the ground truth.
+   - **Others**: 
+     - **Multiple Scenes**: Contains various scenes (e.g., `Bird/`, `Tennis/`, etc.). Each scene consists of four pairs of RGB images and their corresponding ground truth masks.
+     - **Blurred_bg**: This folder includes images with blurred backgrounds and corresponding ground truth occlusion segmentation labels.
+       - **GT**: Contains 88 ground truth occlusion mask.
+       - **Imgs**: Contains 88 blurred background images in JPG format.
+
+2. **Unlabeled Data**:
+   - **DefocusBlurred**: Focused on data related to blurred foreground occlusions.
+     - **Blurred_fg**: Contains 46 video files and `Imgs/'.
+   - **RGB**: Contains regular RGB images and videos.
+     - **Imgs**: 205 JPEG images of various scenes with occlusions.
+     - **Vids**: Includes a total of 214  video files.
+   - **RGBD**: Contains data for scenes with RGB images and depth data.
+     - **MAT files**: These files store all the data values and additional camera information for various samples.
+     - **Othersamples**: Includes additional data samples captured in laboratory.
+
+### Key Dataset Features:
+- **Fence Detection**: Designed for detecting fences or fence-like structures that might occlude objects.
+- **Defocus Blur**: Contains images and videos with blurred objects, likely to challenge detection and segmentation algorithms.
+- **RGBD Data**: Offers depth information alongside RGB images, which can be used for tasks like 3D reconstruction or occlusion handling.
+- **Unlabeled and Labeled Data**: Facilitates both supervised and unsupervised learning tasks. The `Labeled` <a href="https://huggingface.co/datasets/NeuroVizv0yaZ3R/IITKGP_Fence_dataset/tree/main/Labeled" style="color: darkorange;">folder</a>  data provides ground truth occlusion masks, while the `Unlabeled` <a href="https://huggingface.co/datasets/NeuroVizv0yaZ3R/IITKGP_Fence_dataset/tree/main/Unlabeled" style="color: teal;">folder</a> data allows for further experimentation or self-supervised methods.
+
+### Dataset Repository
+
+- **GitHub Repository:** <a href="https://github.com/Moushumi9medhi/Occlusion-Removal" style="color: magenta;">Occlusion-Removal</a>
+- **Paper:** [https://arxiv.org/abs/placeholder]
+  - **Authors:**  [Sankaraganesh Jonna](https://www.linkedin.com/in/ganeshjonna/), Moushumi Medhi, [Rajiv Ranjan Sahay](https://www.iitkgp.ac.in/department/EE/faculty/ee-rajiv)
+
+## Usage
+```bash
+pip install datasets
+
+from datasets import load_dataset
+dataset = load_dataset('NeuroVizv0yaZ3R/IITKGP_Fence_dataset')
+```
+
+## Citation 
+
+**BibTeX:**
+Will be updated soon!
+
+## License
+
+For license details, refer to the [LICENSE](https://huggingface.co/datasets/choosealicense/licenses/blob/main/markdown/apache-2.0.md) file. 
+
+## Acknowledgments
+
+We would like to express our gratitude to **Dr. Sreeja S R** for her valuable contributions to the [Imgs folder](https://huggingface.co/datasets/NeuroVizv0yaZ3R/IITKGP_Fence_dataset/tree/main/Unlabeled/RGB/Imgs) within the RGB directory of the Unlabeled dataset, which greatly enriched its diversity and quality.
+
+
+## Contact
+[[email protected]](mailto:[email protected])
+