update readme

README.md

@@ -33,10 +33,9 @@ To get started with horizon-metrics, make sure you have the necessary dependenci
 
 This is how you can quickly evaluate your horizon prediction models using SEA-AI/horizon-metrics:
 
-```python
-import evaluate
+##### Use artifical data for testing
 
-#Use artificial data for testing or
+```python
 ground_truth_points = [[[0.0, 0.5384765625], [1.0, 0.4931640625]],
                        [[0.0, 0.53796875], [1.0, 0.4928515625]],
                        [[0.0, 0.5374609375], [1.0, 0.4925390625]],
@@ -48,27 +47,34 @@ prediction_points = [[[0.0, 0.5428930956049597], [1.0, 0.4642497615378973]],
                      [[0.0, 0.523573113510805], [1.0, 0.47642688648919496]],
                      [[0.0, 0.5200016849393765], [1.0, 0.4728554579177664]],
                      [[0.0, 0.523573113510805], [1.0, 0.47642688648919496]]]
+```
+
+##### Load data from fiftyone
 
-#Load data from fiftyone
+```python
 sequence = "Sentry_2023_02_Portugal_2023_01_24_19_15_17"
 dataset_name = "SENTRY_VIDEOS_DATASET_QA"
 sequence_view = fo.load_dataset(dataset_name).match(F("sequence") == sequence)
 sequence_view = sequence_view.select_group_slices("thermal_wide")
 
-#Get the ground truth points
 polylines_gt = sequence_view.values("frames.ground_truth_pl")
 ground_truth_points = [
     line["polylines"][0]["points"][0] for line in polylines_gt[0]
     if line is not None
 ]
 
-#Get the predicted points
 polylines_pred = sequence_view.values(
     "frames.ahoy-IR-b2-whales__XAVIER-AGX-JP46_pl")
 prediction_points = [
     line["polylines"][0]["points"][0] for line in polylines_pred[0]
     if line is not None
 ]
+```
+
+##### Calculate horizon metrics
+
+```python
+import evaluate
 
 module = evaluate.load("SEA-AI/horizon-metrics")
 module.add(predictions=ground_truth_points, references=prediction_points)