Drafting optimized metrics

README.md

@@ -2,6 +2,8 @@
 ## Examples
 - [**TBD**] Animated gif of "Empirical DE-CCP" on a drive scene? 
 
+🚩  Checkout demo.ipynb for more details about the results ⚠️
+
 ## Requirements
 - Conda v23.11.0 
 - CUDA v12.0+ (drv N° 525.147.05+)

experiments.py

@@ -16,7 +16,7 @@ from src.conformalizers import (
 )
 
 
-VERSION = "__release"
+VERSION = "___release"
 EPSILONS = np.array([0.01, 0.05, 0.1, 0.2]) #, 0.3, 0.4, 0.5, 0.6, 0.7, 0.8, 0.9])
 
 
@@ -30,12 +30,12 @@ def setup_experiment(epsilons: np.ndarray = EPSILONS) -> Tuple:
     ]
     parameters = [
         {'epsilon': eps,
-         'k_folds': 3, #10,
-         'cal_ratio': 0.15, #0.15,
+         'k_folds': 10,
+         'cal_ratio': 0.15,
          'val_size': 100,
          'iou_threshold': 0.3,
          'confidence_threshold': 0.3,
-         'epochs': 2, #100,
+         'epochs': 100,
          'from_scratch': False,
          'device': torch.device('cuda:0')
          } for eps in epsilons
@@ -74,8 +74,8 @@ if __name__ == "__main__":
         warnings.simplefilter("ignore")
     detectors = [
         CorrelatedDetector(),
-        #CorrelatedDetector(cov_matrix=None),
-        #YOLOv8()
+        CorrelatedDetector(cov_matrix=None),
+        YOLOv8()
     ]
     res = UQEvalResults()
     label = f'UQ_experiments{VERSION}'