From e1b504bca41a9793ed7e88ef14f2e2cbd85724f2 Mon Sep 17 00:00:00 2001 From: aktersnurra Date: Tue, 8 Sep 2020 23:14:23 +0200 Subject: IAM datasets implemented. --- src/text_recognizer/datasets/iam_dataset.py | 134 ++++++++++++++++++++++++++++ 1 file changed, 134 insertions(+) create mode 100644 src/text_recognizer/datasets/iam_dataset.py (limited to 'src/text_recognizer/datasets/iam_dataset.py') diff --git a/src/text_recognizer/datasets/iam_dataset.py b/src/text_recognizer/datasets/iam_dataset.py new file mode 100644 index 0000000..5e47350 --- /dev/null +++ b/src/text_recognizer/datasets/iam_dataset.py @@ -0,0 +1,134 @@ +"""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 torch.utils.data import Dataset + +from text_recognizer.datasets import DATA_DIRNAME +from text_recognizer.datasets.util import _download_raw_dataset + +RAW_DATA_DIRNAME = DATA_DIRNAME / "raw" / "iam" +METADATA_FILENAME = RAW_DATA_DIRNAME / "metadata.toml" +EXTRACTED_DATASET_DIRNAME = RAW_DATA_DIRNAME / "iamdb" + +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(Dataset): + """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() -- cgit v1.2.3-70-g09d2