Add refactor of iam lines

1 files changed, 0 insertions, 133 deletions

diff --git a/text_recognizer/data/iam_dataset.py b/text_recognizer/data/iam_dataset.py
deleted file mode 100644
index a8998b9..0000000
--- a/text_recognizer/data/iam_dataset.py
+++ /dev/null
@@ -1,133 +0,0 @@
-"""Class for loading the IAM dataset, which encompasses both paragraphs and lines, with associated utilities."""
-import os
-from typing import Any, Dict, List
-import zipfile
-
-from boltons.cacheutils import cachedproperty
-import defusedxml.ElementTree as ET
-from loguru import logger
-import toml
-
-from text_recognizer.datasets.util import _download_raw_dataset, DATA_DIRNAME
-
-RAW_DATA_DIRNAME = DATA_DIRNAME / "raw" / "iam"
-METADATA_FILENAME = RAW_DATA_DIRNAME / "metadata.toml"
-EXTRACTED_DATASET_DIRNAME = RAW_DATA_DIRNAME / "iamdb"
-RAW_DATA_DIRNAME.mkdir(parents=True, exist_ok=True)
-
-DOWNSAMPLE_FACTOR = 2  # If images were downsampled, the regions must also be.
-LINE_REGION_PADDING = 0  # Add this many pixels around the exact coordinates.
-
-
-class IamDataset:
-    """IAM dataset.
-
-    "The IAM Lines dataset, first published at the ICDAR 1999, contains forms of unconstrained handwritten text,
-    which were scanned at a resolution of 300dpi and saved as PNG images with 256 gray levels."
-    From http://www.fki.inf.unibe.ch/databases/iam-handwriting-database
-
-    The data split we will use is
-    IAM lines Large Writer Independent Text Line Recognition Task (lwitlrt): 9,862 text lines.
-        The validation set has been merged into the train set.
-        The train set has 7,101 lines from 326 writers.
-        The test set has 1,861 lines from 128 writers.
-        The text lines of all data sets are mutually exclusive, thus each writer has contributed to one set only.
-
-    """
-
-    def __init__(self) -> None:
-        self.metadata = toml.load(METADATA_FILENAME)
-
-    def load_or_generate_data(self) -> None:
-        """Downloads IAM dataset if xml files does not exist."""
-        if not self.xml_filenames:
-            self._download_iam()
-
-    @property
-    def xml_filenames(self) -> List:
-        """List of xml filenames."""
-        return list((EXTRACTED_DATASET_DIRNAME / "xml").glob("*.xml"))
-
-    @property
-    def form_filenames(self) -> List:
-        """List of forms filenames."""
-        return list((EXTRACTED_DATASET_DIRNAME / "forms").glob("*.jpg"))
-
-    def _download_iam(self) -> None:
-        curdir = os.getcwd()
-        os.chdir(RAW_DATA_DIRNAME)
-        _download_raw_dataset(self.metadata)
-        _extract_raw_dataset(self.metadata)
-        os.chdir(curdir)
-
-    @property
-    def form_filenames_by_id(self) -> Dict:
-        """Creates a dictionary with filenames as keys and forms as values."""
-        return {filename.stem: filename for filename in self.form_filenames}
-
-    @cachedproperty
-    def line_strings_by_id(self) -> Dict:
-        """Return a dict from name of IAM form to a list of line texts in it."""
-        return {
-            filename.stem: _get_line_strings_from_xml_file(filename)
-            for filename in self.xml_filenames
-        }
-
-    @cachedproperty
-    def line_regions_by_id(self) -> Dict:
-        """Return a dict from name of IAM form to a list of (x1, x2, y1, y2) coordinates of all lines in it."""
-        return {
-            filename.stem: _get_line_regions_from_xml_file(filename)
-            for filename in self.xml_filenames
-        }
-
-    def __repr__(self) -> str:
-        """Print info about dataset."""
-        return "IAM Dataset\n" f"Number of forms: {len(self.xml_filenames)}\n"
-
-
-def _extract_raw_dataset(metadata: Dict) -> None:
-    logger.info("Extracting IAM data.")
-    with zipfile.ZipFile(metadata["filename"], "r") as zip_file:
-        zip_file.extractall()
-
-
-def _get_line_strings_from_xml_file(filename: str) -> List[str]:
-    """Get the text content of each line. Note that we replace " with "."""
-    xml_root_element = ET.parse(filename).getroot()  # nosec
-    xml_line_elements = xml_root_element.findall("handwritten-part/line")
-    return [el.attrib["text"].replace(""", '"') for el in xml_line_elements]
-
-
-def _get_line_regions_from_xml_file(filename: str) -> List[Dict[str, int]]:
-    """Get the line region dict for each line."""
-    xml_root_element = ET.parse(filename).getroot()  # nosec
-    xml_line_elements = xml_root_element.findall("handwritten-part/line")
-    return [_get_line_region_from_xml_element(el) for el in xml_line_elements]
-
-
-def _get_line_region_from_xml_element(xml_line: Any) -> Dict[str, int]:
-    """Extracts coordinates for each line of text."""
-    # TODO: fix input!
-    word_elements = xml_line.findall("word/cmp")
-    x1s = [int(el.attrib["x"]) for el in word_elements]
-    y1s = [int(el.attrib["y"]) for el in word_elements]
-    x2s = [int(el.attrib["x"]) + int(el.attrib["width"]) for el in word_elements]
-    y2s = [int(el.attrib["y"]) + int(el.attrib["height"]) for el in word_elements]
-    return {
-        "x1": min(x1s) // DOWNSAMPLE_FACTOR - LINE_REGION_PADDING,
-        "y1": min(y1s) // DOWNSAMPLE_FACTOR - LINE_REGION_PADDING,
-        "x2": max(x2s) // DOWNSAMPLE_FACTOR + LINE_REGION_PADDING,
-        "y2": max(y2s) // DOWNSAMPLE_FACTOR + LINE_REGION_PADDING,
-    }
-
-
-def main() -> None:
-    """Initializes the dataset and print info about the dataset."""
-    dataset = IamDataset()
-    dataset.load_or_generate_data()
-    print(dataset)
-
-
-if __name__ == "__main__":
-    main()