add wandb example to readme (#22)

* add wandb example to readme

* fix names

Co-authored-by: Andre Victória Matias <andre.vmatias@gmail.com>

* fix code snippets type

Co-authored-by: Andre Victória Matias <andre.vmatias@gmail.com>

README.md

@@ -12,7 +12,7 @@ Three computer vision approaches are covered: Segmentation, Detection and Classi
 ### For Model Evaluation
 
 This module exports the following functions for model evaluation:
-```
+```python
 from lapixdl.evaluation.evaluate import evaluate_segmentation
 from lapixdl.evaluation.evaluate import evaluate_detection
 from lapixdl.evaluation.evaluate import evaluate_classification
@@ -24,7 +24,7 @@ These iterators must be sorted equaly, assuring that the ground truth and the pr
 
 #### Example of segmentation model evaluation using **PyTorch**:
 
-```
+```python
 from lapixdl.evaluation.evaluate import evaluate_segmentation
 
 classes = ['background', 'object']
@@ -52,11 +52,33 @@ eval = evaluate_segmentation(gt_masks, pred_masks, classes)
 # Shows confusion matrix and returns its Figure and Axes
 fig, axes = eval.show_confusion_matrix()
 ```
+#### Example of how to log the results of LAPiX DL evaluations in the Weights & Biases platform
+About [Weights & Biases](https://docs.wandb.ai/).
+
+```python
+from lapixdl.evaluation.evaluate import evaluate_segmentation
+import wandb
+
+# init wandb ...
+...
+
+eval_test = evaluate_segmentation(gt_masks, pred_masks, categories)
+
+...
+
+# If you want to log everything
+wandb.log({'test_evaluation':  eval_test.to_dict()['By Class']})
+
+# If you want to choose specific categories to log
+selected_cats = ['A', 'B', 'C']
+metrics_by_cat = {k: v for k, v in eval_test.to_dict()['By Class'].items() if k in selected_cats}
+wandb.log({'test_evaluation': metrics_by_cat})
+```
 
 ### For Results Visualization
 
 This module exports the following functions for results visualization:
-```
+```python
 from lapixdl.evaluation.visualize import show_segmentations
 from lapixdl.evaluation.visualize import show_classifications
 from lapixdl.evaluation.visualize import show_detections
@@ -67,13 +89,13 @@ The available color maps are the [ones from matplotlib](https://matplotlib.org/3
 ### For Data Conversion
 
 This module exports the following functions for data conversion:
-```
+```python
 from lapixdl.convert.labelbox import labelbox_to_coco
 ```
 
 #### Example of conversion from **Labelbox** to **COCO** labels format:
 
-```
+```python
 import json
 from lapixdl.convert.labelbox import labelbox_to_coco