Merge branch 'main' of https://arnweb.nl/gitea/arne/EV5_Beeldherk_Bomen

README.md

@@ -67,6 +67,8 @@ $ pip install -e .
 ```bash
 $ python ./src/experiments/dataset.py
 ```
+4. (optional) run the template extraction tool
+5. (optional) run the dataset splitter tool
 
 ### Run CVSuite (for the first time)
 1. Create `config.json` in the `./src/config/` folder and copy the contents of the template
@@ -103,11 +105,35 @@ $ python ./src/helpers/test/knn.py -i ./out/result-(date/time).csv -o ./out/mode
     - `-m` Model to train; `dectree`, `randforest` or `extratree`
     - `-s` Scaler file to use (`.pkl` file)
 ```sh
-python ./src/helpers/test/decision_tree.py -i ./out/result-(date/time).csv -o ./out/models/ -m 'dectree' -s ./out/models/scale_(date/time).pkl
+$ python ./src/helpers/test/decision_tree.py -i ./out/result-(date/time).csv -o ./out/models/ -m 'dectree' -s ./out/models/scale_(date/time).pkl
 ```
 2. The script generates one `.pkl` file based on the chosen model
 3. Edit your `config.json` to include the newly created model
 
+### Template extraction
+> :warning: **Please note:** <br>
+> This tool uses the legacy format for datasets.<br>
+> Images are sorted using folders, instead of by name.
+
+1. Images should have four standard Aruco markers clearly visible
+2. Run the template extraction tool with an input directory as argument
+```sh
+$ python ./src/experiments/template_extraction/script.py ./dataset
+```
+3. The script generates new folders, ending with `_out`
+4. The paths to any failed images are saved in `skipped.txt`
+
+### Dataset splitting
+1. Ensure that the dataset is in `./res/dataset`
+2. Run the dataset splitter tool:
+```sh
+$ python ./src/experiments/dataset.py
+```
+3. Three new folders will be created, containing the following percentage of images:
+    - `./res/dataset/training`, 70%
+    - `./res/dataset/validation`, 20%
+    - `./res/dataset/training`, 10%
+4. Images are split pseudorandomly, thus will create the same datasets on different machines.
 ---
 
 Arne van Iterson<br>