added template extraction to readme
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README.md
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README.md
@ -67,6 +67,8 @@ $ pip install -e .
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```bash
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$ python ./src/experiments/dataset.py
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```
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4. (optional) run the template extraction tool
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5. (optional) run the dataset splitter tool
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### Run CVSuite (for the first time)
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1. Create `config.json` in the `./src/config/` folder and copy the contents of the template
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@ -103,11 +105,23 @@ $ python ./src/helpers/test/knn.py -i ./out/result-(date/time).csv -o ./out/mode
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- `-m` Model to train; `dectree`, `randforest` or `extratree`
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- `-s` Scaler file to use (`.pkl` file)
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```sh
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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
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$ 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
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```
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2. The script generates one `.pkl` file based on the chosen model
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3. Edit your `config.json` to include the newly created model
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### Template extraction
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> :warning: **Please note:** <br>
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> This tool uses the legacy format for datasets.<br>
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> Images are sorted using folders, instead of by name
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1. Images should have four standard Aruco markers clearly visible
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2. Run the template extraction tool with an input directory as argument
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```sh
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$ python ./src/experiments/template_extraction/script.py ./dataset
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```
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3. The script generates new folders, ending with `_out`
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4. The paths to any failed images are saved in `skipped.txt`
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---
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Arne van Iterson<br>
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