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import distutils.util
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import glob
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import os
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import shutil
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import cv2
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import pandas as pd
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from PIL import Image
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from pydicom import dcmread
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from pydicom.fileset import FileSet
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from tqdm import tqdm
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from .volReader import VolFile
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script_dir = os.path.dirname(__file__)
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class Error(Exception):
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"""Base class for exceptions in this module."""
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pass
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def extract_files(dirtoextract, extracted_path, input_format):
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"""Extracts individual image frames from .vol or DICOM files.
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This function scans a directory for source files of a specified format
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and extracts them into a structured output directory as PNG images.
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It handles both .vol files and standard DICOM files. If the
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output directory already contains files, it will prompt the user
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before proceeding to overwrite them.
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Args:
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dirtoextract (str): The root directory to search for source files.
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extracted_path (str): The destination directory where the extracted
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PNG images will be saved.
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input_format (str): The format of the input files. Must be either
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"vol" or "dicom".
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"""
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assert input_format in ["vol", "dicom"], 'Error: input_format must be "vol" or "dicom".'
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proceed = True
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if (os.path.isdir(extracted_path)) and (len(os.listdir(extracted_path)) != 0):
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val = input(
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f"{extracted_path} exists and is not empty. Files may be overwritten. Proceed with extraction? (Y/N)"
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)
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proceed = bool(distutils.util.strtobool(val))
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if proceed:
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print(f"Extracting files from {dirtoextract} into {extracted_path}...")
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if input_format == "vol":
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files_to_extract = glob.glob(os.path.join(dirtoextract, "**/*.vol"), recursive=True)
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for _, line in enumerate(tqdm(files_to_extract)):
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fpath = line.strip("\n")
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vol = VolFile(fpath)
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fpath = fpath.replace("\\", "/")
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path, scan_str = fpath.strip(".vol").rsplit("/", 1)
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extractpath = os.path.join(extracted_path, scan_str.replace("_", "/"))
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os.makedirs(extractpath, exist_ok=True)
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preffix = os.path.join(extractpath, scan_str + "_oct")
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vol.render_oct_scans(preffix)
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elif input_format == "dicom":
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keywords = ["SOPInstanceUID", "PatientID", "ImageLaterality", "SeriesDate"]
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list_of_dicts = []
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dirgen = glob.iglob(os.path.join(dirtoextract, "**/DICOMDIR"), recursive=True)
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for dsstr in dirgen:
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fs = FileSet(dcmread(dsstr))
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fsgenopt = gen_opt_fs(fs)
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for fi in tqdm(fsgenopt):
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dd = dict()
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for key in keywords:
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dd[key] = fi.get(key)
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volpath = os.path.join(extracted_path, f"{fi.SOPInstanceUID}")
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shutil.rmtree(volpath, ignore_errors=True)
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os.mkdir(volpath)
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n = fi.NumberOfFrames
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for i in range(n):
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fname = os.path.join(volpath, f"{fi.SOPInstanceUID}_oct_{i:03d}.png")
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Image.fromarray(fi.pixel_array[i]).save(fname)
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list_of_dicts.append(dd.copy())
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dfoct = pd.DataFrame(list_of_dicts, columns=keywords)
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dfoct.to_csv(os.path.join(extracted_path, "basic_meta.csv"))
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else:
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pass
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def rpd_data(extracted_path):
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"""Generates a dataset list from a directory of extracted image files.
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Scans a directory recursively for PNG images and creates a list of
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dictionaries, one for each image. This format is designed to be compatible
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with Detectron2's `DatasetCatalog` and can be adapted to hold ground truth instances for evaluation.
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Args:
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extracted_path (str): The root directory containing the extracted
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.png image files to be included in the dataset.
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Returns:
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list[dict]: A list where each dictionary represents an image and
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contains its file path, dimensions, and a unique ID.
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"""
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dataset = []
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extracted_files = glob.glob(os.path.join(extracted_path, "**/*.[Pp][Nn][Gg]"), recursive=True)
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print("Generating dataset of images...")
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for fn in tqdm(extracted_files):
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fn_adjusted = fn.replace("\\", "/")
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imageid = fn_adjusted.split("/")[-1]
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im = cv2.imread(fn)
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dat = dict(file_name=fn_adjusted, height=im.shape[0], width=im.shape[1], image_id=imageid)
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dataset.append(dat)
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print(f"Found {len(dataset)} images")
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return dataset
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def gen_opt_fs(fs):
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"""A generator for finding and loading OPT modality DICOM datasets.
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This function filters a pydicom `FileSet` object for instances that have
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the modality set to "OPT" (Ophthalmic Tomography) and yields each one
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as a fully loaded pydicom dataset.
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Args:
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fs (pydicom.fileset.FileSet): The pydicom FileSet to search through.
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Yields:
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pydicom.dataset.FileDataset: A loaded DICOM dataset for each instance
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with the "OPT" modality found in the FileSet.
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"""
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for instance in fs.find(Modality="OPT"):
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ds = instance.load()
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yield ds
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