diff --git a/ethology/annotations/io.py b/ethology/annotations/io.py
deleted file mode 100644
index 1cf137e..0000000
--- a/ethology/annotations/io.py
+++ /dev/null
@@ -1,195 +0,0 @@
-"""Module for reading and writing manually labelled annotations."""
-
-import json
-from pathlib import Path
-
-import pandas as pd
-from movement.validators.files import ValidFile
-
-from ethology.annotations.json_schemas import COCO_SCHEMA, VIA_SCHEMA
-from ethology.annotations.validators import (
-    ValidCOCOJSON,
-    ValidJSON,
-    ValidVIAJSON,
-)
-
-STANDARD_DF_COLUMNS = [
-    "annotation_id",
-    "image_filename",
-    "image_id",
-    "x_min",
-    "y_min",
-    "width",
-    "height",
-    "supercategory",
-    "category",
-]
-
-
-def df_from_via_json_file(file_path: Path) -> pd.DataFrame:
-    """Validate and read untracked VIA JSON file.
-
-    The data is formatted as an untracked annotations DataFrame.
-
-    Parameters
-    ----------
-    file_path : Path
-        Path to the untracked VIA JSON file.
-
-    Returns
-    -------
-    pd.DataFrame
-        Untracked annotations DataFrame.
-
-    """
-    # Run validators
-    file = ValidFile(
-        file_path, expected_permission="r", expected_suffix=[".json"]
-    )
-    json_file = ValidJSON(path=file.path, schema=VIA_SCHEMA)
-    via_untracked_file = ValidVIAJSON(json_file.path)
-
-    # Read as standard dataframe
-    return _df_from_validated_via_json_file(via_untracked_file.path)
-
-
-def df_from_coco_json_file(file_path: Path) -> pd.DataFrame:
-    """Validate and read untracked COCO JSON file.
-
-    The data is formatted as an untracked annotations DataFrame.
-
-    Parameters
-    ----------
-    file_path : Path
-        Path to the untracked COCO JSON file.
-
-    Returns
-    -------
-    pd.DataFrame
-        Untracked annotations DataFrame.
-
-    """
-    # Run validators
-    file = ValidFile(
-        file_path, expected_permission="r", expected_suffix=[".json"]
-    )
-    json_file = ValidJSON(path=file.path, schema=COCO_SCHEMA)
-    coco_untracked_file = ValidCOCOJSON(json_file.path)
-
-    # Read as standard dataframe
-    return _df_from_validated_coco_json_file(coco_untracked_file.path)
-
-
-def _df_from_validated_via_json_file(file_path):
-    """Read VIA JSON file as standard untracked annotations DataFrame."""
-    # Read validated json as dict
-    with open(file_path) as file:
-        data_dict = json.load(file)
-
-    # Prepare data
-    image_metadata_dict = data_dict["_via_img_metadata"]
-    via_image_id_list = data_dict[
-        "_via_image_id_list"
-    ]  # ordered list of the keys in image_metadata_dict
-
-    # map filename to keys in image_metadata_dict
-    map_filename_to_via_img_id = {
-        img_dict["filename"]: ky
-        for ky, img_dict in image_metadata_dict.items()
-    }
-
-    # Build standard dataframe
-    list_rows = []
-    # loop thru images
-    for _, img_dict in image_metadata_dict.items():
-        # loop thru annotations in the image
-        for region in img_dict["regions"]:
-            region_shape = region["shape_attributes"]
-            region_attributes = region["region_attributes"]
-
-            row = {
-                "image_filename": img_dict["filename"],
-                "x_min": region_shape["x"],
-                "y_min": region_shape["y"],
-                "width": region_shape["width"],
-                "height": region_shape["height"],
-                "supercategory": list(region_attributes.keys())[
-                    0
-                ],  # takes first key as supercategory
-                "category": region_attributes[
-                    list(region_attributes.keys())[0]
-                ],
-            }
-
-            # append annotations to df
-            list_rows.append(row)
-
-    df = pd.DataFrame(
-        list_rows,
-        # columns=list(row.keys()),  # do I need this?
-    )
-
-    # add image_id column
-    df["image_id"] = df["image_filename"].apply(
-        lambda x: via_image_id_list.index(map_filename_to_via_img_id[x])
-    )
-
-    # add annotation_id column based on index
-    df["annotation_id"] = df.index
-
-    # reorder columns to match standard
-    df = df.reindex(columns=STANDARD_DF_COLUMNS)
-
-    return df
-
-
-def _df_from_validated_coco_json_file(file_path: Path) -> pd.DataFrame:
-    """Read COCO JSON file as standard untracked annotations DataFrame."""
-    # Read validated json as dict
-    with open(file_path) as file:
-        data_dict = json.load(file)
-
-    # Prepare data
-    map_image_id_to_filename = {
-        img_dict["id"]: img_dict["file_name"]
-        for img_dict in data_dict["images"]
-    }
-
-    map_category_id_to_category_data = {
-        cat_dict["id"]: (cat_dict["name"], cat_dict["supercategory"])
-        for cat_dict in data_dict["categories"]
-    }
-
-    # Build standard dataframe
-    list_rows = []
-    for annot_dict in data_dict["annotations"]:
-        annotation_id = annot_dict["id"]
-        # image data
-        image_id = annot_dict["image_id"]
-        image_filename = map_image_id_to_filename[image_id]
-
-        # bbox data
-        x_min, y_min, width, height = annot_dict["bbox"]
-
-        # class data
-        category_id = annot_dict["category_id"]
-        category, supercategory = map_category_id_to_category_data[category_id]
-
-        row = {
-            "annotation_id": annotation_id,
-            "image_filename": image_filename,
-            "image_id": image_id,
-            "x_min": x_min,
-            "y_min": y_min,
-            "width": width,
-            "height": height,
-            "supercategory": supercategory,
-            "category": category,
-        }
-
-        list_rows.append(row)
-
-    df = pd.DataFrame(list_rows)
-    df.reindex(columns=STANDARD_DF_COLUMNS)
-
-    return df