Update README.md

README.md

@@ -17,6 +17,10 @@ size_categories:
 
 CAFOSat is a remote sensing dataset designed for identifying and classifying Concentrated Animal Feeding Operations (CAFOs) across various U.S. states. It includes high-resolution image patches, infrastructure annotations, bounding boxes, and experimental train-test splits for multiple configurations.
 
+## 🔗 Resources
+
+- **GitHub Repository:** [oishee-hoque/CAFOSat](https://github.com/oishee-hoque/CAFOSat)
+- **Explore the Dataset:** [CAFOSat Data Loader and Examples](https://github.com/oishee-hoque/CAFOSat/tree/main/data_loader)
 ---
 
 ## Dataset Structure
@@ -27,7 +31,7 @@ The dataset is organized into extracted folders originally packaged as `.tar.gz`
   (e.g., `IA_filtered/`, `AL_filtered/`)
 - `negative_samples/`: Verified non-CAFO examples
 - `barn/`, `manure_pond/`, `others/`: Augmented synthetic patches by infrastructure type
-- `cafosat.csv`: Master metadata file with labels, bounding boxes, and split flags
+- `CAFOSat.csv`: Master metadata file with labels, bounding boxes, and split flags
 
 All image paths referenced in the CSV point to these extracted folders. 
 📄 Example data loader available [here](https://github.com/oishee-hoque/CAFOSat/tree/main/data_loader).
@@ -38,32 +42,49 @@ All image paths referenced in the CSV point to these extracted folders.
 ## 🔖 Image File Reference (`patch_file`)
 
 Each row in the metadata includes a `patch_file` field that provides the relative path to the associated image file.
-Each `patch_file` is a pointer into a compressed archive using Hugging Face's streaming format:
 
 Example:  
 -`IA_filtered.tar.gz::IA_filtered/crop_4517_patch_10147_Swine_Nursery_IA.tif`
 - `barn.tar.gz::`barn/aug_patch_00123.tif`
 - `negative_sample.tar.gz::`barn/neg_patch_00098.tif`
-
-This format indicates the image is located inside `IA_filtered.tar.gz` under the subpath shown. This field is automatically interpreted by Hugging Face as an image using the `datasets.Image()` feature, so image previews and loading work out of the box.
-
 ---
 
 ## Features
 
-| Column        | Description                                           |
-|---------------|-------------------------------------------------------|
-| `patch_file`  | Path to the image file                                |
-| `label`       | Integer label for class (0–6)                         |
-| `barn`, `manure_pond`, `grazing_area`, `others` | Binary infra flags       |
-| `geom_bbox`   | Bounding box coordinates `[x1, y1, x2, y2]`           |
-| `category`    | Class name (e.g., Swine, Dairy)                       |
-| `state`       | U.S. state of the patch                               |
-| `verified_label` | Human-verified CAFO type                           |
-| `CAFO_UNIQUE_ID` | Unique identifier for facility                     |
-| `image_type`  | `original`, `augmented`, `negative`, etc.             |
+| Column                                | Description                                                                 |
+|---------------------------------------|-----------------------------------------------------------------------------|
+| `patch_file`                          | Path to the image file                                                     |
+| `label`                               | Integer label for class (0–6)                                              |
+| `barn`, `manure_pond`, `grazing_area`, `others` | Binary flags indicating infrastructure types                              |
+| `geom_bbox`                           | Bounding box coordinates `[x1, y1, x2, y2]`                                 |
+| `geometry`                            | Geospatial polygon outlining the CAFO region                               |
+| `poly_crs`                            | Coordinate reference system used for `geometry`                            |
+| `patch_crs`                           | Coordinate reference system used for the image patch                       |
+| `category`                            | CAFO class name (e.g., Swine, Dairy)                                       |
+| `state`                               | U.S. state where the patch is located                                      |
+| `verified_label`                      | Boolean indicating if the label is human-verified                          |
+| `CAFO_UNIQUE_ID`                      | Unique identifier for each CAFO facility                                   |
+| `image_type`                          | Image variant type: `augmented` else real                                  |
+| `orig_patch_file`                     | Name/path of the original patch (applicable if the image_type is `augmented`)       |
+| `prompt`                              | Text prompt or description for generative/semantic use (if applicable)     |
+| `weak_x`, `weak_y`                    | Collected CAFO center coordinates                                          |
+| `refined_x`, `refined_y`              | Refined CAFO center coordinates                                            |
+| `patch_res`                           | Spatial resolution of the patch in meters per pixel 
 | `split columns` | Flags for different train/test/val splits           |
 
+---
+## 🧪 Train/Test/Val Split Flags
+
+These are boolean-like flags (`True`/`False`) that indicate inclusion in various dataset splits:
+
+- `cafosat_verified_training_train`, `cafosat_verified_training_test`, `cafosat_verified_training_val`
+- `cafosat_all_training_*`
+- `cafosat_training_set1_*`, `set2_*`
+- `cafosat_merged_training_*`
+- `cafosat_augmented_training_*`
+
+Each flag is a binary indicator (`1` = in split, `0` = excluded).
+
 ---
 
 ## Labels
@@ -80,26 +101,14 @@ This format indicates the image is located inside `IA_filtered.tar.gz` under the
 
 ---
 
-## Splits
-
-Multiple experimental train-test split columns are provided in the CSV:
-
-- `cafosat_verified_training_train`, `cafosat_verified_training_test`, `cafosat_verified_training_val`
-- `cafosat_all_training_*`
-- `cafosat_training_set1_*`, `set2_*`
-- `cafosat_merged_training_*`
-- `cafosat_augmented_training_*`
-
-Each flag is a binary indicator (`1` = in split, `0` = excluded).
-
----
 
-## Intended Use
+## 📌 Intended Use
 
-- CAFO detection and classification
-- Agricultural infrastructure mapping
-- Weak supervision, semi-supervised learning
-- Remote sensing benchmark development
+- **CAFO detection and classification** – Identify and categorize CAFO facilities from aerial imagery.
+- **CAFO area detection with bounding box** – Localize CAFOs using annotated bounding box coordinates.
+- **Agricultural infrastructure mapping** – Map features like barns, manure ponds, and grazing areas.
+- **Weak supervision and semi-supervised learning** – Leverage partially labeled data for model development.
+- **Remote sensing benchmark development** – Support standardized evaluation for remote sensing tasks.
 
 ---