Update README.md

README.md

@@ -24,7 +24,7 @@ size_categories:
 PM25Vision (PM25V) is a large-scale dataset for estimating air quality (PM2.5) from street-level imagery. It pairs **Mapillary** photos with **World Air Quality Index (WAQI)** PM2.5 records, covering 2014–2025, 3,261 monitoring stations, and 11,114 cleaned and balanced images.
 
 ## Tasks
-- **Regression**: Predict continuous PM2.5 values.  
+- **Regression**: Predict continuous PM2.5 **AQI** values.  
 - **Classification**: Predict discrete AQI levels.
 
 ## Baseline Results
@@ -54,20 +54,20 @@ The dataset is organized into two main splits: **train** and **test**, each cont
 
 Each row in `metadata.csv` contains:
 
-| Field          | Type    | Description                                                                          |
-|----------------|---------|--------------------------------------------------------------------------------------|
-| **`image_id`** | int64   | Unique image identifier (from Mapillary).                                            |
-| `station_id`   | int64   | WAQI monitoring station ID.                                                          |
-| `captured_at`  | object  | Date when the image was captured (YYYY-MM-DD).                                       |
-| `camera_angle` | float64 | Camera orientation (if available).                                                   |
-| `longitude`    | float64 | Longitude of the station.                                                            |
-| `latitude`     | float64 | Latitude of the station.                                                             |
-| `quality_score`| float64 | Image quality score from Mapillary (if available).                                   |
-| `downloaded_at`| object  | Timestamp when the sample was downloaded.                                            |
-| **`pm25`**     | float64 | Average PM2.5 value of the day that the image was captured(the label, in AQI value). |
-| `filename`     | object  | Image filename, located in the `images/` directory.                                  |
-| `quality`      | object  | ResNet18 classified label for image quality (e.g., `good` or `bad`).                 |
-| `pm25_bin`     | object  | Discrete AQI level label (e.g., `0–50`, `51–100`, etc.).                             |
+| Field          | Type    | Description                                                          |
+|----------------|---------|----------------------------------------------------------------------|
+| `**image_id**` | int64   | Unique image identifier (from Mapillary).                            |
+| `station_id`   | int64   | WAQI monitoring station ID.                                          |
+| `captured_at`  | object  | Date when the image was captured (YYYY-MM-DD).                       |
+| `camera_angle` | float64 | Camera orientation (if available).                                   |
+| `longitude`    | float64 | Longitude of the station.                                            |
+| `latitude`     | float64 | Latitude of the station.                                             |
+| `quality_score`| float64 | Image quality score from Mapillary (if available).                   |
+| `downloaded_at`| object  | Timestamp when the sample was downloaded.                            |
+| `**pm25**`     | float64 | Average PM2.5 AQI value of the day that the image was captured.      |
+| `filename`     | object  | Image filename, located in the `images/` directory.                  |
+| `quality`      | object  | ResNet18 classified label for image quality (e.g., `good` or `bad`). |
+| `pm25_bin`     | object  | Discrete AQI level label (e.g., `0–50`, `51–100`, etc.).             |
 
 ### Splits