diff --git a/qim3d/io/load.py b/qim3d/io/load.py
index e5037333df475c708c59edc479af8f5627e902fe..5095e2fe1611b8547d44c59c7fe01ebdbfcd3674 100644
--- a/qim3d/io/load.py
+++ b/qim3d/io/load.py
@@ -24,10 +24,7 @@ class DataLoader:
         load_tiff(path): Load a TIFF file from the specified path.
         load_h5(path): Load an HDF5 file from the specified path.
         load_tiff_stack(path): Load a stack of TIFF files from the specified path.
-<<<<<<< HEAD
-=======
         load_txrm(path): Load a TXRM/TXM/XRM file from the specified path
->>>>>>> main
         load(path): Load a file or directory based on the given path.
 
     Raises:
@@ -44,11 +41,7 @@ class DataLoader:
         Args:
             path (str): The path to the file or directory.
             virtual_stack (bool, optional): Specifies whether to use virtual
-<<<<<<< HEAD
-            stack when loading TIFF and HDF5 files. Default is False.
-=======
             stack when loading files. Default is False.
->>>>>>> main
             dataset_name (str, optional): Specifies the name of the dataset to be loaded
             in case multiple dataset exist within the same file. Default is None (only for HDF5 files)
             return_metadata (bool, optional): Specifies whether to return metadata or not. Default is False (only for HDF5 files)
@@ -95,8 +88,6 @@ class DataLoader:
             ValueError: If the specified dataset_name is not found or is invalid.
             ValueError: If the dataset_name is not specified in case of multiple datasets in the HDF5 file
             ValueError: If no datasets are found in the file.
-<<<<<<< HEAD
-=======
         """
 
         # Read file
@@ -175,98 +166,11 @@ class DataLoader:
 
         Returns:
             numpy.ndarray: The loaded volume as a NumPy array.
->>>>>>> main
 
         Raises:
             ValueError: If the 'contains' argument is not specified.
             ValueError: If the 'contains' argument matches multiple TIFF stacks in the directory
         """
-<<<<<<< HEAD
-        # Read file
-        f = h5py.File(path, "r")
-        data_keys = self._get_h5_dataset_keys(f)
-        datasets = []
-        metadata = {}
-        for key in data_keys:
-            if (
-                f[key].ndim > 1
-            ):  # Data is assumed to be a dataset if it is two dimensions or more
-                datasets.append(key)
-            if f[key].attrs.keys():
-                metadata[key] = {
-                    "value": f[key][()],
-                    **{attr_key: val for attr_key, val in f[key].attrs.items()},
-                }
-
-        # Only one dataset was found
-        if len(datasets) == 1:
-            if self.dataset_name:
-                log.info(
-                    "'dataset_name' argument is unused since there is only one dataset in the file"
-                )
-            name = datasets[0]
-            vol = f[name]
-
-        # Multiple datasets were found
-        elif len(datasets) > 1:
-            if self.dataset_name in datasets:  # Provided dataset name is valid
-                name = self.dataset_name
-                vol = f[name]
-            else:
-                if self.dataset_name:  # Dataset name is provided
-                    similar_names = difflib.get_close_matches(
-                        self.dataset_name, datasets
-                    )  # Find closest matching name if any
-                    if similar_names:
-                        suggestion = similar_names[0]  # Get the closest match
-                        raise ValueError(
-                            f"Invalid dataset name. Did you mean '{suggestion}'?"
-                        )
-                    else:
-                        raise ValueError(
-                            f"Invalid dataset name. Please choose between the following datasets: {datasets}"
-                        )
-                else:
-                    raise ValueError(
-                        f"Found multiple datasets: {datasets}. Please specify which of them that you want to load with the argument 'dataset_name'"
-                    )
-
-        # No datasets were found
-        else:
-            raise ValueError(f"Did not find any data in the file: {path}")
-
-        if not self.virtual_stack:
-            vol = vol[()]  # Load dataset into memory
-            f.close()
-        else:
-            log.info("Using virtual stack")
-
-        log.info("Loaded the following dataset: %s", name)
-        log.info("Loaded shape: %s", vol.shape)
-        log.info("Using %s of memory", sizeof(sys.getsizeof(vol)))
-
-        if self.return_metadata:
-            return vol, metadata
-        else:
-            return vol
-        
-    def load_tiff_stack(self, path):
-        """Load a stack of TIFF files from the specified path.
-
-        Args:
-            path (str): The path to the stack of TIFF files.
-
-        Returns:
-            numpy.ndarray: The loaded volume as a NumPy array.
-
-        Raises:
-            ValueError: If the 'contains' argument is not specified.
-            ValueError: If the 'contains' argument matches multiple TIFF stacks in the directory
-
-        """
-=======
-
->>>>>>> main
         if not self.contains:
             raise ValueError(
                 "Please specify a part of the name that is common for the TIFF file stack with the argument 'contains'"
@@ -287,11 +191,7 @@ class DataLoader:
             raise ValueError(f"The provided part of the filename for the TIFF stack matches multiple TIFF stacks: {unique_names}.\nPlease provide a string that is unique for the TIFF stack that is intended to be loaded")
     
 
-<<<<<<< HEAD
-        vol = tifffile.imread([os.path.join(path, file) for file in tiff_stack])
-=======
         vol = tifffile.imread([os.path.join(path, file) for file in tiff_stack],out='memmap')
->>>>>>> main
 
         if not self.virtual_stack:
             vol = np.copy(vol) # Copy to memory
@@ -304,8 +204,6 @@ class DataLoader:
 
         return vol
     
-<<<<<<< HEAD
-=======
     def load_txrm(self,path):
         """Load a TXRM/XRM/TXM file from the specified path.
 
@@ -340,7 +238,6 @@ class DataLoader:
         else:
             return vol
     
->>>>>>> main
     def load(self, path):
         """
         Load a file or directory based on the given path.
@@ -389,21 +286,12 @@ class DataLoader:
             else:
                 raise ValueError("Invalid path")
 
-<<<<<<< HEAD
-    def _get_h5_dataset_keys(self, f):
-        keys = []
-        f.visit(
-            lambda key: keys.append(key) if isinstance(f[key], h5py.Dataset) else None
-        )
-        return keys
-=======
 def _get_h5_dataset_keys(f):
     keys = []
     f.visit(
         lambda key: keys.append(key) if isinstance(f[key], h5py.Dataset) else None
     )
     return keys
->>>>>>> main
 
 
 def load(path, virtual_stack=False, dataset_name=None, return_metadata=False, contains=None, **kwargs):
@@ -416,11 +304,7 @@ def load(path, virtual_stack=False, dataset_name=None, return_metadata=False, co
         stack when loading TIFF and HDF5 files. Default is False.
         dataset_name (str, optional): Specifies the name of the dataset to be loaded
         in case multiple dataset exist within the same file. Default is None (only for HDF5 files)
-<<<<<<< HEAD
-        return_metadata (bool, optional): Specifies whether to return metadata or not. Default is False (only for HDF5 files)
-=======
         return_metadata (bool, optional): Specifies whether to return metadata or not. Default is False (only for HDF5 and TXRM files)
->>>>>>> main
         contains (str, optional): Specifies a part of the name that is common for the TIFF file stack to be loaded (only for TIFF stacks)
         **kwargs: Additional keyword arguments to be passed
         to the DataLoader constructor.
diff --git a/qim3d/viz/__init__.py b/qim3d/viz/__init__.py
index a9507bc03e9d5b4baf8e8b5b62822d1a5ea8e8b0..1c36c157b724c6ce86efd512b03b400395ae6bbe 100644
--- a/qim3d/viz/__init__.py
+++ b/qim3d/viz/__init__.py
@@ -1,6 +1,2 @@
-<<<<<<< HEAD
-from .img import grid_pred, grid_overview
 from .visualizations import plot_metrics
-=======
 from .img import grid_pred, grid_overview, slice_viz
->>>>>>> main