Update documentation

docs/usage/datasets/analyze.md

@@ -4,8 +4,6 @@
 
 Use the `teklia-dan dataset analyze` command to analyze a dataset. This will display statistics in [Markdown](https://www.markdownguide.org/) format.
 
-The available arguments are:
-
 | Parameter       | Description                      | Type           | Default |
 | --------------- | -------------------------------- | -------------- | ------- |
 | `--labels`      | Path to the `labels.json` file.  | `pathlib.Path` |         |

docs/usage/evaluate/index.md

 # Evaluation
 
+## Description
+
 Use the `teklia-dan evaluate` command to evaluate a trained DAN model.
 
 To evaluate DAN on your dataset:
 
 1. Create a JSON configuration file. You can base the configuration file off the training one. Refer to the [dedicated page](../train/config.md) for a description of parameters.
 1. Run `teklia-dan evaluate --config path/to/your/config.json`.
-1. Evaluation results for every split are available in the `results` subfolder of the output folder indicated in your configuration.
-1. A metrics Markdown table, providing results for each evaluated split, is also printed in the console (see table example below).
 
-### Example output - Metrics Markdown table
+This will, for each evaluated split:
+
+1. Create a YAML file with the evaluation results in the `results` subfolder of the `training.output_folder` indicated in your configuration.
+1. Print in the console a metrics Markdown table (see [table example below](#htr-evaluation)).
+1. Print in the console a Nerval metrics Markdown table, if the `dataset.tokens` parameter in your configuration is defined (see [table example below](#htr-and-ner-evaluation)).
+
+| Parameter            | Description                                                                                  | Type           | Default |
+| -------------------- | -------------------------------------------------------------------------------------------- | -------------- | ------- |
+| `--config`           | Path to the configuration file.                                                              | `pathlib.Path` |         |
+| `--nerval-threshold` | Distance threshold for the match between gold and predicted entity during Nerval evaluation. | `float`        | `0.3`   |
+
+## Example output
+
+### HTR evaluation
+
+| Split | CER (HTR-NER) | CER (HTR) | WER (HTR-NER) | WER (HTR) | WER (HTR no punct) |
+| :---: | :-----------: | :-------: | :-----------: | :-------: | :----------------: |
+| train |       x       |     x     |       x       |     x     |         x          |
+|  val  |       x       |     x     |       x       |     x     |         x          |
+| test  |       x       |     x     |       x       |     x     |         x          |
+
+### HTR and NER evaluation
 
 | Split | CER (HTR-NER) | CER (HTR) | WER (HTR-NER) | WER (HTR) | WER (HTR no punct) | NER |
 | :---: | :-----------: | :-------: | :-----------: | :-------: | :----------------: | :-: |
 | train |       x       |     x     |       x       |     x     |         x          |  x  |
 |  val  |       x       |     x     |       x       |     x     |         x          |  x  |
 | test  |       x       |     x     |       x       |     x     |         x          |  x  |
+
+#### train
+
+|   tag   | predicted | matched | Precision | Recall | F1  | Support |
+| :-----: | :-------: | :-----: | :-------: | :----: | :-: | :-----: |
+| Surname |     x     |    x    |     x     |   x    |  x  |    x    |
+|   All   |     x     |    x    |     x     |   x    |  x  |    x    |
+
+#### val
+
+|   tag   | predicted | matched | Precision | Recall | F1  | Support |
+| :-----: | :-------: | :-----: | :-------: | :----: | :-: | :-----: |
+| Surname |     x     |    x    |     x     |   x    |  x  |    x    |
+|   All   |     x     |    x    |     x     |   x    |  x  |    x    |
+
+#### test
+
+|   tag   | predicted | matched | Precision | Recall | F1  | Support |
+| :-----: | :-------: | :-----: | :-------: | :----: | :-: | :-----: |
+| Surname |     x     |    x    |     x     |   x    |  x  |    x    |
+|   All   |     x     |    x    |     x     |   x    |  x  |    x    |

docs/usage/predict/index.md

 # Prediction
 
-Use the `teklia-dan predict` command to apply a trained DAN model on an image.
-
 ## Description
 
+Use the `teklia-dan predict` command to apply a trained DAN model on an image.
+
 | Parameter                   | Description                                                                                                                           | Type           | Default       |
 | --------------------------- | ------------------------------------------------------------------------------------------------------------------------------------- | -------------- | ------------- |
 | `--image-dir`               | Path to the folder where the images to predict are stored. Must not be provided with `--image`.                                       | `pathlib.Path` |               |