Update BioMap.py

BioMap.py

@@ -52,6 +52,7 @@ _URLS = {
     "default": "https://huggingface.co/great-new-dataset-first_domain.zip",
 }
 
+norm_values = {'B01': {'mean': 0.12478869, 'std': 0.024433358, 'min': 1e-04, 'max': 1.8808, 'p1': 0.0787, 'p99': 0.1946}, 'B02': {'mean': 0.13480005, 'std': 0.02822557, 'min': 1e-04, 'max': 2.1776, 'p1': 0.0925, 'p99': 0.2216}, 'B03': {'mean': 0.16031432, 'std': 0.032037303, 'min': 1e-04, 'max': 2.12, 'p1': 0.1035, 'p99': 0.2556}, 'B04': {'mean': 0.1532097, 'std': 0.038628064, 'min': 1e-04, 'max': 2.0032, 'p1': 0.1023, 'p99': 0.2816}, 'B05': {'mean': 0.20312776, 'std': 0.04205057, 'min': 0.0422, 'max': 1.7502, 'p1': 0.1178, 'p99': 0.319}, 'B06': {'mean': 0.32636437, 'std': 0.07139242, 'min': 0.0502, 'max': 1.7245, 'p1': 0.1633, 'p99': 0.519}, 'B07': {'mean': 0.36605212, 'std': 0.08555025, 'min': 0.0616, 'max': 1.7149, 'p1': 0.1776, 'p99': 0.6076}, 'B08': {'mean': 0.3811653, 'std': 0.092815965, 'min': 1e-04, 'max': 1.7488, 'p1': 0.1691, 'p99': 0.646}, 'B8A': {'mean': 0.3910436, 'std': 0.0896364, 'min': 0.055, 'max': 1.688, 'p1': 0.1871, 'p99': 0.6386}, 'B09': {'mean': 0.3910644, 'std': 0.0836445, 'min': 0.0012, 'max': 1.7915, 'p1': 0.2124, 'p99': 0.6241}, 'B11': {'mean': 0.2917373, 'std': 0.07472579, 'min': 0.0953, 'max': 1.648, 'p1': 0.1334, 'p99': 0.4827}, 'B12': {'mean': 0.21169408, 'std': 0.05880649, 'min': 0.0975, 'max': 1.6775, 'p1': 0.115, 'p99': 0.3872}}
 
 # TODO: Name of the dataset usually matches the script name with CamelCase instead of snake_case
 class NewDataset(datasets.GeneratorBasedBuilder):
@@ -73,6 +74,7 @@ class NewDataset(datasets.GeneratorBasedBuilder):
 
     BUILDER_CONFIGS = [
         datasets.BuilderConfig(name="default", version=VERSION, description="This part of my dataset covers a first domain"),
+        datasets.BuilderConfig(name="unnormalized", version=VERSION, description="This part of my dataset covers a first domain"),
     ]
 
     DEFAULT_CONFIG_NAME = "default"  # It's not mandatory to have a default configuration. Just use one if it make sense.
@@ -101,6 +103,16 @@ class NewDataset(datasets.GeneratorBasedBuilder):
             citation=_CITATION,
         )
 
+    def denormalize_s2(self,patch):
+        r,g,b = patch[3],patch[2],patch[1]
+		res = []
+		for band, band_value in zip(['B04','B03','B02'],[r,g,b]) :
+				p1, p99 = norm_values[band]['p1'], norm_values[band]['p99']
+				band_value = (p99 - p1) * band_value + p1
+				res.append(band_value)
+        patch[3],patch[2],patch[1] = res
+		return patch
+        
     def _split_generators(self, dl_manager):
         # TODO: This method is tasked with downloading/extracting the data and defining the splits depending on the configuration
         # If several configurations are possible (listed in BUILDER_CONFIGS), the configuration selected by the user is in self.config.name
@@ -140,11 +152,17 @@ class NewDataset(datasets.GeneratorBasedBuilder):
     # method parameters are unpacked from `gen_kwargs` as given in `_split_generators`
     def _generate_examples(self, filepath, split):
         for i,d in enumerate(self.ds[split]):
-            yield i, {
-                'input': d["input"],
-                'label': d["label"]
-            }
-
-
-
+            if self.config.name == "default":
+                yield i, {
+                    'input': d["input"],
+                    'label': d["label"]
+                }
+                
+            elif self.config.name == "unnormalized":
+                yield i, {
+                    'input': self.denormalize_s2(d["input"]),
+                    'label': d["label"]
+                }
+    
+