diff --git a/.github/workflows/test_and_deploy.yml b/.github/workflows/test_and_deploy.yml
index ac0a507..271c9c2 100644
--- a/.github/workflows/test_and_deploy.yml
+++ b/.github/workflows/test_and_deploy.yml
@@ -21,46 +21,44 @@ jobs:
     runs-on: ${{ matrix.platform }}
     strategy:
       matrix:
-        platform: [ubuntu-latest, windows-latest, macos-latest]
+        platform: [ubuntu-latest]
         python-version: ['3.10']
-
+    defaults:
+      run:
+        shell: bash -el {0}
     steps:
-      - uses: actions/checkout@v2
-      - name: Set up Python ${{ matrix.python-version }}
-        uses: actions/setup-python@v2
+      - uses: actions/checkout@v3
+      - name: Set up conda ${{ matrix.python-version }}
+        uses: conda-incubator/setup-miniconda@v2
         with:
+          mamba-version: "*"
+          activate-environment: napari-boxmanager
+          channel-priority: true
           python-version: ${{ matrix.python-version }}
-
-      # these libraries enable testing on Qt on linux
-      - uses: tlambert03/setup-qt-libs@v1
-
-      # strategy borrowed from vispy for installing opengl libs on windows
-      - name: Install Windows OpenGL
-        if: runner.os == 'Windows'
-        run: |
-          git clone --depth 1 https://github.com/pyvista/gl-ci-helpers.git
-          powershell gl-ci-helpers/appveyor/install_opengl.ps1
-
-      # note: if you need dependencies from conda, considering using
-      # setup-miniconda: https://github.com/conda-incubator/setup-miniconda
-      # and
-      # tox-conda: https://github.com/tox-dev/tox-conda
+          channels: conda-forge, defaults
+          environment-file: conda_env.yml
+      - run: conda --version
+      - run: conda init bash
+      - run: |
+          which python
       - name: Install dependencies
         run: |
           python -m pip install --upgrade pip
-          python -m pip install setuptools tox tox-gh-actions
-
-      # this runs the platform-specific tests declared in tox.ini
-      - name: Test with tox
-        uses: GabrielBB/xvfb-action@v1
-        with:
-          run: python -m tox
+          pip install setuptools setuptools_scm pylint tox tox-gh-actions pytest pytest-coverage twine build
+          pip install .
+      - name: Debug Info
+        run: |
+          which python
+          pip freeze
+      #- name: Analysing the code with pylint  DEACTIVATED BECAUSE IT THROWS A LOT OF PYQT errors oO
+      #  run: |
+      #    pylint -E $(git ls-files '*.py')
+      - name: Tests
+        run: |
+          pytest -v --cov=./ --cov-report=xml --cov-config=.coveragerc
         env:
           PLATFORM: ${{ matrix.platform }}
 
-      - name: Coverage
-        uses: codecov/codecov-action@v2
-
   deploy:
     # this will run when you have tagged a commit, starting with "v*"
     # and requires that you have put your twine API key in your
diff --git a/conda_env.yml b/conda_env.yml
new file mode 100644
index 0000000..9f49be4
--- /dev/null
+++ b/conda_env.yml
@@ -0,0 +1,17 @@
+name: napari-boxmanager
+channels:
+  - conda-forge
+  - defaults
+dependencies:
+  - python=3.10
+  - napari>=0.4.17
+  - pyqt
+  - tifffile
+  - numpy
+  - matplotlib
+  - pip
+  - pip:
+      - pystardb>=0.4.2
+  - scipy
+  - tqdm
+  - pandas[version='>=2']
diff --git a/reader_backup/_tests/test_box.py b/reader_backup/_tests/test_box.py
deleted file mode 100644
index ec92e67..0000000
--- a/reader_backup/_tests/test_box.py
+++ /dev/null
@@ -1,104 +0,0 @@
-import os
-import pathlib
-
-import pandas
-import pytest
-
-import box_manager.readers.box as brb
-
-TEST_DATA = pathlib.Path(os.path.dirname(__file__), "test_data")
-
-
-@pytest.mark.parametrize("file_name", ["2d_center.box", "2d_center_float.box"])
-def test_read_box_file_center_correct_coord_values(file_name):
-    box_file = pathlib.Path(TEST_DATA, file_name)
-    box_data = brb.read(box_file)
-
-    expected = pandas.DataFrame(
-        {
-            "x": [24, 36, 78],
-            "y": [40, 62, 51],
-            "box_x": [0, 0, 0],
-            "box_y": [0, 0, 0],
-            "filename": box_file,
-        }
-    )
-    pandas.testing.assert_frame_equal(box_data, expected)
-
-
-def test_read_box_file_left_correct_coord_values():
-    file_name = "2d_left.box"
-    box_file = pathlib.Path(TEST_DATA, file_name)
-    box_data = brb.read(box_file)
-
-    expected = pandas.DataFrame(
-        {
-            "x": [14, 26, 68],
-            "y": [35, 57, 46],
-            "box_x": [20, 20, 20],
-            "box_y": [10, 10, 10],
-            "filename": box_file,
-        }
-    )
-    pandas.testing.assert_frame_equal(box_data, expected)
-
-
-def test_read_box_file_empty_expect_empty_list():
-    box_file = pathlib.Path(TEST_DATA, "2d_empty.box")
-    box_data = brb.read(box_file)
-
-    expected = pandas.DataFrame(
-        columns=["x", "y", "box_x", "box_y", "filename"]
-    )
-    pandas.testing.assert_frame_equal(box_data, expected, check_dtype=False)
-
-
-def test_read_box_file_corrupt_column_expect_error():
-    box_file = pathlib.Path(TEST_DATA, "2d_corrupt_unqual_columns.box")
-    with pytest.raises(brb.BoxFileNumberOfColumnsError):
-        brb.read(box_file)
-
-
-def test_read_box_file_corrupt_string_expect_error():
-    box_file = pathlib.Path(TEST_DATA, "2d_corrupt_has_string.box")
-    with pytest.raises(ValueError):
-        brb.read(box_file)
-
-
-@pytest.mark.parametrize(
-    "params", [[[10, 10, 10], [0, 0, 0]], [[30, 35, 40]] * 2]
-)
-def test_prepare_napari_box_file_center_correct_coord_values(params):
-    expected_size, box_size = params
-    print
-    input_df = pandas.DataFrame(
-        {
-            "x": [
-                24 - box_size[0] // 2,
-                36 - box_size[1] // 2,
-                78 - box_size[2] // 2,
-            ],
-            "y": [
-                40 - box_size[0] // 2,
-                62 - box_size[1] // 2,
-                51 - box_size[2] // 2,
-            ],
-            "box_x": box_size,
-            "box_y": box_size,
-            "filename": "test",
-        }
-    )
-    expected_df = pandas.DataFrame(
-        {
-            "x": [40, 62, 51],
-            "y": [24, 36, 78],
-            "boxsize": expected_size,
-            "sort_idx": "test",
-            "grp_idx": "test",
-        }
-    )
-    data, coords_idx, metrics_idx, kwargs = brb.prepare_napari(input_df)
-    pandas.testing.assert_frame_equal(data, expected_df)
-    assert coords_idx == ["x", "y"]
-    assert metrics_idx == ["boxsize"]
-    assert kwargs == {"out_of_slice_display": False}
diff --git a/reader_backup/_tests/test_data b/reader_backup/_tests/test_data
deleted file mode 120000
index 077a737..0000000
--- a/reader_backup/_tests/test_data
+++ /dev/null
@@ -1 +0,0 @@
-../../../../test_data
\ No newline at end of file
diff --git a/reader_backup/_tests/test_init.py b/reader_backup/_tests/test_init.py
deleted file mode 100644
index d927ca1..0000000
--- a/reader_backup/_tests/test_init.py
+++ /dev/null
@@ -1,15 +0,0 @@
-import glob
-import os
-
-import box_manager.readers as bmr
-
-
-def test_valid_functions_correct():
-
-    expected = []
-    for module in glob.iglob(f"{os.path.dirname(__file__)}/../*.py"):
-        if os.path.basename(module) in bmr._ignore_list:
-            continue
-        expected.append(f".{os.path.splitext(os.path.basename(module))[0]}")
-
-    assert sorted(expected) == list(sorted(bmr.valid_readers.keys()))
diff --git a/reader_backup/_tests/test_interface.py b/reader_backup/_tests/test_interface.py
deleted file mode 100644
index dd14993..0000000
--- a/reader_backup/_tests/test_interface.py
+++ /dev/null
@@ -1,118 +0,0 @@
-import os
-import pathlib
-
-import numpy
-import pandas
-
-import box_manager.readers as nrt
-
-TEST_DATA = pathlib.Path(os.path.dirname(__file__), "test_data")
-
-
-def test_to_napari_file_correct_returns():
-    tlpkl_file = pathlib.Path(TEST_DATA, "valid.tlpkl")
-
-    points1, points2 = nrt.to_napari_coordinates(tlpkl_file, nrt.valid_readers[".tlpkl"])
-    assert all([len(entry) == 3 for entry in (points1, points2)])
-
-    x = [86, 88, 6, 24, 78, 46, 30, 60, 76, 76, 70, 66, 30, 76]
-    y = [26, 2, 94, 40, 52, 58, 62, 86, 16, 60, 82, 44, 18, 94]
-    z = [98, 44, 92, 50, 48, 72, 64, 44, 92, 58, 48, 18, 28, 10]
-    points = pandas.DataFrame(
-        {
-            "x": z,
-            "y": y,
-            "z": x,
-        }
-    )
-    pandas.testing.assert_frame_equal(points1[0], points.iloc[:8])
-    pandas.testing.assert_frame_equal(points2[0], points.iloc[8:])
-
-    size = [18, 40, 90, 67, 89, 88, 82, 82, 76, 51, 11, 282, 248, 244]
-    metric_best = numpy.array(
-        [
-            0.639648,
-            0.945801,
-            0.947754,
-            0.951172,
-            0.953125,
-            0.955566,
-            0.956055,
-            0.956543,
-            0.534180,
-            0.538574,
-            0.550781,
-            0.880371,
-            0.885742,
-            0.888184,
-        ],
-        dtype=numpy.float32,
-    )
-    width = [37] * len(x)
-    height = [40] * len(x)
-    depth = [50] * len(x)
-
-    boxsize = [numpy.array([width, height, depth]).mean().mean()] * len(x)
-
-    metadata = {
-        "id": 1,
-        "size_min": min(size[:8]),
-        "size_max": max(size[:8]),
-        "metric_min": min(metric_best[:8]),
-        "metric_max": max(metric_best[:8]),
-        "boxsize_min": min(boxsize[:8]),
-        "boxsize_max": max(boxsize[:8]),
-    }
-    assert list(sorted(metadata.keys())) == list(
-        sorted(points1[1]["metadata"].keys())
-    )
-    for key in metadata.keys():
-        val1 = metadata[key]
-        val2 = points1[1]["metadata"][key]
-        numpy.testing.assert_array_almost_equal(val1, val2)
-
-    metadata = {
-        "id": 2,
-        "size_min": min(size[8:]),
-        "size_max": max(size[8:]),
-        "metric_min": min(metric_best[8:]),
-        "metric_max": max(metric_best[8:]),
-        "boxsize_min": min(boxsize[8:]),
-        "boxsize_max": max(boxsize[8:]),
-    }
-    assert list(sorted(metadata.keys())) == list(
-        sorted(points2[1]["metadata"].keys())
-    )
-    for key in metadata.keys():
-        val1 = metadata[key]
-        val2 = points2[1]["metadata"][key]
-        numpy.testing.assert_array_almost_equal(val1, val2)
-
-    features = {
-        "size": size[:8],
-        "metric": metric_best[:8],
-        "boxsize": boxsize[:8],
-    }
-    assert list(sorted(features.keys())) == list(
-        sorted(points1[1]["features"].keys())
-    )
-    for key in features.keys():
-        val1 = features[key]
-        val2 = points1[1]["features"][key]
-        numpy.testing.assert_array_almost_equal(val1, val2)
-
-    features = {
-        "size": size[8:],
-        "metric": metric_best[8:],
-        "boxsize": boxsize[8:],
-    }
-    assert list(sorted(features.keys())) == list(
-        sorted(points2[1]["features"].keys())
-    )
-    for key in features.keys():
-        val1 = features[key]
-        val2 = points2[1]["features"][key]
-        numpy.testing.assert_array_almost_equal(val1, val2)
-
-    numpy.testing.assert_array_equal(boxsize[:8], points1[1]["size"])
-    numpy.testing.assert_array_equal(boxsize[8:], points2[1]["size"])
diff --git a/reader_backup/_tests/test_tlpkl.py b/reader_backup/_tests/test_tlpkl.py
deleted file mode 100644
index c7a98e8..0000000
--- a/reader_backup/_tests/test_tlpkl.py
+++ /dev/null
@@ -1,104 +0,0 @@
-import os
-import pathlib
-
-import numpy
-import pandas
-
-import box_manager.readers.tlpkl as nrt
-
-TEST_DATA = pathlib.Path(os.path.dirname(__file__), "test_data")
-
-
-def test_correct_read():
-    tlpkl_file = pathlib.Path(TEST_DATA, "valid.tlpkl")
-    test_data = nrt.read(tlpkl_file)
-
-    x = [86, 88, 6, 24, 78, 46, 30, 60, 76, 76, 70, 66, 30, 76]
-    y = [26, 2, 94, 40, 52, 58, 62, 86, 16, 60, 82, 44, 18, 94]
-    z = [98, 44, 92, 50, 48, 72, 64, 44, 92, 58, 48, 18, 28, 10]
-    size = [18, 40, 90, 67, 89, 88, 82, 82, 76, 51, 11, 282, 248, 244]
-    metric_best = numpy.array(
-        [
-            0.639648,
-            0.945801,
-            0.947754,
-            0.951172,
-            0.953125,
-            0.955566,
-            0.956055,
-            0.956543,
-            0.534180,
-            0.538574,
-            0.550781,
-            0.880371,
-            0.885742,
-            0.888184,
-        ],
-        dtype=numpy.float32,
-    )
-    width = [37] * len(x)
-    height = [40] * len(x)
-    depth = [50] * len(x)
-    predicted_class = [1] * 8 + [2] * 6
-    predicted_class_name = ["cluster_2.pkl"] * 8 + ["cluster_3.pkl"] * 6
-    expected = pandas.DataFrame(
-        {
-            "X": x,
-            "Y": y,
-            "Z": z,
-            "size": size,
-            "metric_best": metric_best,
-            "predicted_class": predicted_class,
-            "predicted_class_name": predicted_class_name,
-            "width": width,
-            "height": height,
-            "depth": depth,
-        }
-    )
-    pandas.testing.assert_frame_equal(test_data[expected.columns], expected)
-
-
-def test_correct_prepare_napari():
-    x = [86, 88, 6]
-    y = [26, 2, 94]
-    z = [98, 44, 92]
-    size = [18, 40, 90]
-    metric_best = numpy.array(
-        [0.639648, 0.945801, 0.947754], dtype=numpy.float32
-    )
-    width = [37] * len(x)
-    height = [40] * len(x)
-    depth = [50] * len(x)
-    input_df = pandas.DataFrame(
-        {
-            "Z": z,
-            "Y": y,
-            "X": x,
-            "size": size,
-            "metric_best": metric_best,
-            "width": width,
-            "height": height,
-            "depth": depth,
-            "predicted_class_name": ["classx.pkl"] * 3,
-            "predicted_class": [0] * 3,
-        }
-    )
-    expected = pandas.DataFrame(
-        {
-            "z": x,
-            "y": y,
-            "x": z,
-            "size": size,
-            "metric": metric_best,
-            "boxsize": numpy.mean(numpy.array([width, height, depth])),
-            "grp_idx": ["classx.pkl"] * 3,
-            "sort_idx": [0] * 3,
-        }
-    )
-    test_df, test_coords, test_metadata, kwargs = nrt.prepare_napari(input_df)
-    assert test_coords == ["x", "y", "z"]
-    assert test_metadata == ["metric", "size", "boxsize"]
-    pandas.testing.assert_frame_equal(
-        test_df[expected.columns.values], expected
-    )
-    assert kwargs == {}
diff --git a/reader_backup/cbox.py b/reader_backup/cbox.py
deleted file mode 100644
index 463c062..0000000
--- a/reader_backup/cbox.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import typing
-
-import pandas as pd
-
-if typing.TYPE_CHECKING:
-    import pathlib
-
-    import numpy as np
-
-
-def read(path: "pathlib.Path") -> pd.DataFrame:
-    raise NotImplementedError
-
-
-def prepare_napari(
-    path: "pathlib.Path",
-) -> "tuple[np.ndarray, dict[str, typing.Any], dict[str, typing.Any], str]":
-    raise NotImplementedError
diff --git a/reader_backup/star.py b/reader_backup/star.py
deleted file mode 100644
index 463c062..0000000
--- a/reader_backup/star.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import typing
-
-import pandas as pd
-
-if typing.TYPE_CHECKING:
-    import pathlib
-
-    import numpy as np
-
-
-def read(path: "pathlib.Path") -> pd.DataFrame:
-    raise NotImplementedError
-
-
-def prepare_napari(
-    path: "pathlib.Path",
-) -> "tuple[np.ndarray, dict[str, typing.Any], dict[str, typing.Any], str]":
-    raise NotImplementedError
diff --git a/reader_backup/tepkl.py b/reader_backup/tepkl.py
deleted file mode 100644
index 463c062..0000000
--- a/reader_backup/tepkl.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import typing
-
-import pandas as pd
-
-if typing.TYPE_CHECKING:
-    import pathlib
-
-    import numpy as np
-
-
-def read(path: "pathlib.Path") -> pd.DataFrame:
-    raise NotImplementedError
-
-
-def prepare_napari(
-    path: "pathlib.Path",
-) -> "tuple[np.ndarray, dict[str, typing.Any], dict[str, typing.Any], str]":
-    raise NotImplementedError
diff --git a/reader_backup/tlpkl.py b/reader_backup/tlpkl.py
deleted file mode 100644
index e329a11..0000000
--- a/reader_backup/tlpkl.py
+++ /dev/null
@@ -1,55 +0,0 @@
-import os
-import typing
-
-import pandas as pd
-
-if typing.TYPE_CHECKING:
-    pass
-
-
-class DimZMissingWarning(Warning):
-    pass
-
-
-def read(path: "os.PathLike") -> pd.DataFrame:
-    """
-    Read a tlpkl conform file into memory.
-    tlpkl files need to have their coordinates for the Z and X dimension inverted.
-
-    :param path: Path of the file to read information from.
-    :type path: Path object or str
-
-    :return: DataFrame containing the coordinates, box size, metrics, and cluster size
-    :rtype: Pandas DataFrame
-    """
-    pandas_data: pd.DataFrame = pd.read_pickle(path)
-
-    pandas_data["X"] = pandas_data["X"].astype(int)
-    pandas_data["Y"] = pandas_data["Y"].astype(int)
-    pandas_data["Z"] = pandas_data["Z"].astype(int)
-
-    return pandas_data
-
-
-def prepare_napari(
-    input_df: pd.DataFrame,
-) -> tuple[pd.DataFrame, list[str], list[str], typing.Any]:
-    coords_idx = ["x", "y", "z"]
-    metric_idx = ["metric", "size", "boxsize"]
-    util_idx = ["sort_idx", "grp_idx"]
-    output_data: pd.DataFrame = pd.DataFrame(
-        columns=coords_idx + metric_idx + util_idx
-    )
-
-    output_data["x"] = input_df["Z"]
-    output_data["y"] = input_df["Y"]
-    output_data["z"] = input_df["X"]
-    output_data["metric"] = input_df["metric_best"]
-    output_data["size"] = input_df["size"]
-    output_data["boxsize"] = input_df[["height", "width", "depth"]].mean(
-        axis=1
-    )
-    output_data["sort_idx"] = input_df["predicted_class"]
-    output_data["grp_idx"] = input_df["predicted_class_name"]
-
-    return output_data, coords_idx, metric_idx, {}
diff --git a/reader_backup/tmpkl.py b/reader_backup/tmpkl.py
deleted file mode 100644
index 463c062..0000000
--- a/reader_backup/tmpkl.py
+++ /dev/null
@@ -1,18 +0,0 @@
-import typing
-
-import pandas as pd
-
-if typing.TYPE_CHECKING:
-    import pathlib
-
-    import numpy as np
-
-
-def read(path: "pathlib.Path") -> pd.DataFrame:
-    raise NotImplementedError
-
-
-def prepare_napari(
-    path: "pathlib.Path",
-) -> "tuple[np.ndarray, dict[str, typing.Any], dict[str, typing.Any], str]":
-    raise NotImplementedError
diff --git a/reader_backup/to_napari_backup.txt b/reader_backup/to_napari_backup.txt
deleted file mode 100644
index 28c8f88..0000000
--- a/reader_backup/to_napari_backup.txt
+++ /dev/null
@@ -1,58 +0,0 @@
-
-#def to_napari(
-#    input_data: "os.PathLike | pd.DataFrame",
-#    reader: ReaderInterface | None = None,
-#) -> "list[tuple[npt.ArrayLike, dict[str, typing.Any], str]]":
-#    """
-#    Read a tlpkl conform file into memory to use within napari.
-#
-#    :param path: Path of the file to read information from.
-#    :type path: pathlib.Path or str
-#
-#    :return: Data to create a point, i.e., coords, point_kwargs, and type
-#    :rtype: list[tuple[npt.ArrayLike, dict[str, typing.Any], str]]
-#    """
-#    if isinstance(input_data, (os.PathLike, str)):
-#        input_data = reader.read(input_data)
-#    data, coords_idx, metadata_idx, extra_kwargs = reader.prepare_napari(
-#        input_data
-#    )
-#
-#    colors = mcm.get_cmap("gist_rainbow")
-#    n_classes = np.unique(data["grp_idx"]).size
-#    n_classes = np.maximum(n_classes, 2)  # Avoid zero division error
-#
-#    output_list: "list[tuple[npt.ArrayLike, dict[str, typing.Any], str]]" = []
-#    for idx, (cluster_name, cluster_df) in enumerate(
-#        data.sort_values(by=["sort_idx"]).groupby("grp_idx", sort=False)
-#    ):
-#        color = colors(idx / (n_classes - 1))
-#        metadata = {
-#            f"{entry}_{func.__name__}": func(cluster_df[entry])
-#            for func in [min, max]
-#            for entry in metadata_idx
-#        }
-#        metadata["id"] = cluster_df["sort_idx"].iloc[0]
-#
-#        # to_numpy currently needed. Should be fixed in 0.4.16rc8
-#        features = {
-#            entry: cluster_df[entry].to_numpy() for entry in metadata_idx
-#        }
-#
-#        kwargs = {
-#            "edge_color": [color],
-#            "face_color": "transparent",
-#            "symbol": "disc",
-#            "edge_width": 2,
-#            "edge_width_is_relative": False,
-#            "size": cluster_df["boxsize"],
-#            "out_of_slice_display": True,
-#            "opacity": 0.5,
-#            "name": cluster_name,
-#            "metadata": metadata,
-#            "features": features,
-#        }
-#        kwargs.update(extra_kwargs)
-#        output_list.append((cluster_df[coords_idx], kwargs, "points"))
-#
-#    return output_list
diff --git a/setup.cfg b/setup.cfg
index c04d386..51c5692 100644
--- a/setup.cfg
+++ b/setup.cfg
@@ -29,6 +29,10 @@ install_requires =
     numpy <=1.23.5
     pystardb>=0.4.2
     pandas
+    pyqt5
+    scipy
+    tifffile
+    tqdm
 python_requires = >=3.10
 include_package_data = True
 package_dir =
diff --git a/src/box_manager/_tests/_dummy_test.py b/src/box_manager/_tests/_dummy_test.py
deleted file mode 100644
index 077934e..0000000
--- a/src/box_manager/_tests/_dummy_test.py
+++ /dev/null
@@ -1,2 +0,0 @@
-def test_dumm():
-    pass
diff --git a/src/box_manager/io/interface.py b/src/box_manager/io/interface.py
index 502695f..beb80f4 100644
--- a/src/box_manager/io/interface.py
+++ b/src/box_manager/io/interface.py
@@ -26,7 +26,7 @@ def to_napari(
     def get_valid_extensions(self) -> list[str]:
         ...
 
-    def has_shapes(path: os.PathLike) -> bool:
+    def has_shapes(self, path: os.PathLike) -> bool:
         ...
 
     def from_napari(