feat: implement comprehensive land cover classification pipeline with model benchmarking and experiment logging

2026-07-17 18:54:25 +07:00
parent a258db54cd
commit abab846884
69 changed files with 155558 additions and 105 deletions
@@ -0,0 +1,8 @@
+import joblib
+import numpy as np
+cache_file = "dataset_cache/training_data_2d.joblib"
+data = joblib.load(cache_file)
+X = np.array(data['X'])
+b2 = X[:, 0, :, :]
+print("Zeros in B2:", np.sum(b2 == 0) / b2.size)
+print("X shape:", X.shape)