Updated README.md to include W&B logging changes

README.md

@@ -288,6 +288,45 @@ fig.show()
 
 ![Confidence Curve](assets/example_confidence_curves.png)
 
+## W&B logging
+When you use **module.wandb()**, it is possible to log the detection metrics values for each model in Weights and Bias (W&B). The W&B key is stored as a Secret in this repository.
+
+### Params
+- **wandb_project** - Name of the W&B project (Default: `'detection_metrics'`)
+
+```python
+import evaluate
+import logging
+from seametrics.payload.processor import PayloadProcessor
+
+logging.basicConfig(level=logging.WARNING)
+
+# Configure your dataset and model details
+processor = PayloadProcessor(
+    dataset_name="SAILING_PANOPTIC_DATASET_QA_REVIEWED",
+    gt_field="ground_truth_det",
+    models=["ahoy-b2-IR"],
+    data_type="thermal",
+    slices = ['thermal_right', 'thermal_left', 'thermal_narrow', 'thermal_wide'],
+)
+
+AREA_RNGS = [[0, 1e5**2],
+            [0**2, 6**2],
+            [6**2, 12**2],
+            [12**2, 1e5**2]]
+AREA_NAMES = ["all", "small", "medium", "large"]
+area_ranges_tuples = list(zip(AREA_NAMES, AREA_RNGS))
+
+# Evaluate using SEA-AI/det-metrics
+module = evaluate.load("SEA-AI/det-metrics", payload=processor.payload, area_ranges_tuples=area_ranges_tuples)
+results = module.compute()
+
+# Log the results on W&B.
+module.wandb(results)
+
+```
+
+![image/png](https://cdn-uploads.huggingface.co/production/uploads/65a9139f0237119dc5363462/nUbYLwNiOUBDmCBX383kg.png)
 
 ## Further References