Improve dataset card: Add task categories, code link, and sample usage

This PR enhances the dataset card for the WiCount dataset by:
- Adding `task_categories` (`time-series-forecasting`, `time-series-classification`) and relevant `tags` (`wireless-sensing`, `csi`, `people-counting`, `wifi`) to the metadata for better searchability and categorization on the Hub.
- Adding `language: en` to the metadata.
- Including a direct link to the main GitHub repository (`https://github.com/RS2002/CSI-BERT2`) for easier access to the associated code.
- Removing the auto-generated description line "The description is generated by Grok3.".
- Introducing a "Sample Usage" section with code snippets for pre-training, fine-tuning, and inference, directly derived from the project's GitHub README, to guide users on how to utilize the dataset with the CSI-BERT2 framework.

README.md

@@ -1,10 +1,22 @@
-# WiCount
+---
+language:
+- en
+task_categories:
+- time-series-forecasting
+- time-series-classification
+tags:
+- wireless-sensing
+- csi
+- people-counting
+- wifi
+---
 
-The description is generated by Grok3.
+# WiCount
 
 ## Dataset Description
 
-- **Repository:** [CSI-BERT2/WiCount at main · RS2002/CSI-BERT2](https://github.com/RS2002/CSI-BERT2/tree/main/WiCount)
+- **Repository (WiCount subdirectory):** [CSI-BERT2/WiCount at main · RS2002/CSI-BERT2](https://github.com/RS2002/CSI-BERT2/tree/main/WiCount)
+- **Code:** [https://github.com/RS2002/CSI-BERT2](https://github.com/RS2002/CSI-BERT2)
 - **Paper:** [CSI-BERT2: A BERT-inspired Framework for Efficient CSI Prediction and Classification in Wireless Communication and Sensing](https://arxiv.org/abs/2412.06861)
 - **Contact:** [[email protected]](mailto:[email protected])  
 - **Collectors:** Zijian Zhao, Tingwei Chen  
@@ -13,6 +25,48 @@ The description is generated by Grok3.
   The WiCount dataset contains synchronized Channel State Information (CSI), Received Signal Strength Indicator (RSSI), and timestamp data collected using ESP32-S3 devices for WiFi-based people number estimation in a meeting room scenario. The dataset includes samples for estimating the number of people (0–3) in the environment.
 - **Tasks:** People Number Estimation
 
+## Sample Usage
+
+To use this dataset with the `CSI-BERT2` code, first clone the repository:
+
+```bash
+git clone https://github.com/RS2002/CSI-BERT2
+cd CSI-BERT2
+```
+
+Then you can use the provided scripts for pre-training, fine-tuning, and inference. Replace `<data path>` with the path to the WiCount dataset downloaded from Hugging Face.
+
+### Pre-training
+
+```bash
+python pretrain.py --GAN --data_path <data path>
+```
+If you do not want to use the discriminator, you can omit the `--GAN` flag.
+
+### Fine-tuning for CSI Prediction
+
+```bash
+python prediction.py --GAN --data_path <data path> --parameters <fold path of the whole pre-trained models>
+```
+
+### Fine-tuning for CSI Sensing Task (e.g., People Number Estimation)
+
+For the WiCount dataset, use `task "people"`.
+
+```bash
+python finetune.py --data_path <data path> --class_num <class num> --task "people" --path <parameter path of the backbone> --mode <mode>
+```
+The `mode` parameter can be set as `0`, `1`, or `2`, corresponding to three experiments in the paper:
+- `0`: Training Set (100Hz), Testing Set (100Hz)
+- `1`: Training Set (100Hz+50Hz), Testing Set (100Hz+50Hz)
+- `2`: Training Set (100Hz), Testing Set (50Hz)
+
+### Inference for CSI Prediction
+
+```bash
+python prediction.py --data_path <data path> --parameters <fold path of the whole pretrained models> --eval_percent <the percentage of CSI sequence to be predicted>
+```
+
 ## Dataset Structure
 
 ### Data Instances
@@ -35,7 +89,7 @@ Each instance is a `.csv` file representing a 60-second sample with the followin
 | local_timestamp | ESP32 local time                                             |
 | rssi            | Received Signal Strength Indicator                           |
 | data            | CSI data (104 numbers, representing 52 subcarriers as complex values) |
-| Other columns   | Additional ESP32 metadata (e.g., MAC address, MCS details)   |
+| Other columns   | Additional ESP32 metadata (e.g., MAC address, MCS details)   |\
 
 ### Data Splits