def METHOD_NAME():
    """Loads the fridge object detection dataset.
    return: pandas dataframe with image paths and labels
    rtype: pd.DataFrame
    """
    # create data folder if it doesnt exist.
    os.makedirs("data", exist_ok=True)
    # download data
    download_url = ("https://cvbp-secondary.z19.web.core.windows.net/" +
                    "datasets/object_detection/odFridgeObjects.zip")
    data_file = "./odFridgeObjects.zip"
    request_file.urlretrieve(download_url, filename=data_file)
    # extract files
    with ZipFile(data_file, "r") as zip:
        print("extracting files...")
        zip.extractall(path="./data")
        print("done")
    # delete zip file
    os.remove(data_file)
    labels = load_fridge_object_detection_dataset_labels()
    # get all file names into a pandas dataframe with the labels
    data = pd.DataFrame(columns=["image", "label"])
    for i, file in enumerate(os.listdir("./data/odFridgeObjects/" + "images")):
        image_path = "./data/odFridgeObjects/" + "images" + "/" + file
        data = data.append({"image": image_path,
                            "label": labels[i]},  # folder
                           ignore_index=True)
    return data