drac: save_to_gallery: include 'max_value' parameter to take into account all images value.

src/tomwer/core/process/drac/dracbase.py

@@ -123,7 +123,10 @@ class DracDatasetBase:
         }
 
     def save_to_gallery(
-        self, output_file_name: str, image: numpy.ndarray | DataUrl
+        self,
+        output_file_name: str,
+        image: numpy.ndarray | DataUrl,
+        max_value: int | None = None,
     ) -> None:
         format = self.gallery_output_format
         overwrite = self.gallery_overwrite
@@ -140,10 +143,12 @@ class DracDatasetBase:
         elif image.ndim != 2:
             raise ValueError(f"only 2D grayscale image are handled. Get {image.shape}")
 
+        if max_value is None:
+            max_value = image.max()
         # clamp data in 0-256
         image = image.astype(numpy.float32)
         image = Binning._bin_data(data=image, binning=binning)
-        image *= 255.0 / image.max()
+        image *= 255.0 / max_value
 
         img = Image.fromarray(image, mode=None)
         img = img.convert("L")

src/tomwer/core/process/drac/processeddataset.py

@@ -102,6 +102,7 @@ class IcatReconstructedVolumeDataset(DracDatasetBase):
         gallery_dir = self.get_gallery_dir()
         volume = self.tomo_obj
         slices = volume.get_slices(slices=self.get_slices_to_extract())
+        slices_stack = numpy.concatenate(list([slice_ for slice_ in slices.values()]))
         for (axis, slice_index), slice_ in slices.items():
             self.save_to_gallery(
                 output_file_name=self.get_output_file_name(
@@ -111,6 +112,7 @@ class IcatReconstructedVolumeDataset(DracDatasetBase):
                     volume=volume,
                 ),
                 image=slice_,
+                max_value=numpy.max(slices_stack),
             )
 
     @staticmethod