Update biomassters.py

datasets/biomassters.py

@@ -8,16 +8,7 @@
 from .utils import read_tif
 from utils.registry import DATASET_REGISTRY
 
-s1_min = np.array([-25 , -62 , -25, -60], dtype="float32")
-s1_max = np.array([ 29 ,  28,  30,  22 ], dtype="float32")
-s1_mm = s1_max - s1_min
-s2_max = np.array(
-    [19616., 18400., 17536., 17097., 16928., 16768., 16593., 16492., 15401., 15226.,   255.],
-    dtype="float32",
-)
-IMG_SIZE = (256, 256)
-
-def read_imgs(multi_temporal, temp , fname, data_dir):
+def read_imgs(multi_temporal, temp , fname, data_dir, img_size):
     imgs_s1, imgs_s2, mask = [], [], []
     if multi_temporal:
         month_list = list(range(12))
@@ -34,18 +25,16 @@ def read_imgs(multi_temporal, temp , fname, data_dir):
             img_s1 = imread(s1_filepath)
             m = img_s1 == -9999
             img_s1 = img_s1.astype("float32")
-            img_s1 = (img_s1 - s1_min) / s1_mm
             img_s1 = np.where(m, 0, img_s1)
         else:            
-            img_s1 = np.zeros(IMG_SIZE + (4,), dtype="float32")
+            img_s1 = np.zeros((img_size, img_size) + (4,), dtype="float32")
 
         s2_filepath = data_dir.joinpath(s2_fname)
         if s2_filepath.exists():
             img_s2 = imread(s2_filepath)
             img_s2 = img_s2.astype("float32")
-            img_s2 = img_s2 / s2_max
         else:            
-            img_s2 = np.zeros(IMG_SIZE + (11,), dtype="float32")
+            img_s2 = np.zeros((img_size, img_size) + (11,), dtype="float32")
 
         img_s1 = np.transpose(img_s1, (2, 0, 1))
         img_s2 = np.transpose(img_s2, (2, 0, 1))
@@ -70,6 +59,7 @@ def __init__(self, cfg, split):
         self.multi_temporal = cfg['multi_temporal']
         self.temp = cfg['temporal']
         self.split = split
+        self.img_size = cfg['img_size']
 
         self.data_path = pathlib.Path(self.root_path).joinpath(f"{split}_Data_list.csv")
         self.id_list = pd.read_csv(self.data_path)['chip_id']
@@ -84,7 +74,7 @@ def __getitem__(self, index):
         chip_id = self.id_list.iloc[index]
         fname = str(chip_id)+'_agbm.tif'
 
-        imgs_s1, imgs_s2, mask = read_imgs(self.multi_temporal, self.temp, fname, self.dir_features)
+        imgs_s1, imgs_s2, mask = read_imgs(self.multi_temporal, self.temp, fname, self.dir_features, self.img_size)
         with rasterio.open(self.dir_labels.joinpath(fname)) as lbl:
             target = lbl.read(1)
         target = np.nan_to_num(target)