<commit_before>import numpy as np
import logging
import configargparse as argparse
import glob
from skimage.external import tifffile
import matplotlib.pyplot as plt
import matplotlib
from math import ceil
import copy

def edges_visualisation(options):
    '''
    Script for visualising the WRONG EDGES signalled by the CTC evaluation tool in TRA_log.txt.
    For this we show raw data, segmentation, the segmentation after tracking and the groundtruth for frame t and t+1.

    Note! Everything has to be in CTC-Format!!

    The edges to be added will be shown in Cyan in the groundtruth.
    The redudant edges to be deleted in tomato orange in the tracking result.
    The wrong semantics will be shown in gold in the tracking result.

    The output images for all problematic frames will be written in the ouptut directory. If this directory
    is not specified, then the results open in normal pyplot pop-up windows.
    '''

    if options.output == None:
        logging.getLogger('wrong_edges_visualisation.py').info("Figures will open in pop-up windows. Specify an output path if you want to save them all.")

    with open(options.txt_path) as txt:
        content = txt.readlines()

    edges_to_be_added = []
    redundant_edges = []
    incorrect_semantics = []
    problematic_frames = []
    set_redundant_edges = False<commit_msg>Fix typo<commit_after>import numpy as np
import logging
import configargparse as argparse
import glob
from skimage.external import tifffile
import matplotlib.pyplot as plt
import matplotlib
from math import ceil
import copy

def edges_visualisation(options):
    '''
    Script for visualising the WRONG EDGES signalled by the CTC evaluation tool in TRA_log.txt.
    For this we show raw data, segmentation, the segmentation after tracking and the groundtruth for frame t and t+1.

    Note! Everything has to be in CTC-Format!!

    The edges to be added will be shown in Cyan in the groundtruth.
    The redundant edges to be deleted in tomato orange in the tracking result.
    The wrong semantics will be shown in gold in the tracking result.

    The output images for all problematic frames will be written in the ouptut directory. If this directory
    is not specified, then the results open in normal pyplot pop-up windows.
    '''

    if options.output == None:
        logging.getLogger('wrong_edges_visualisation.py').info("Figures will open in pop-up windows. Specify an output path if you want to save them all.")

    with open(options.txt_path) as txt:
        content = txt.readlines()

    edges_to_be_added = []
    redundant_edges = []
    incorrect_semantics = []
    problematic_frames = []
    set_redundant_edges = False
{'fraction_non_alphanumeric': 0.05196733481811433, 'fraction_numerical': 0.0007423904974016332, 'mean_word_length': 3.5833333333333335, 'pattern_counts': {'":': 0, '<': 3, '<?xml version=': 0, '>': 3, 'https://': 0, 'lorem ipsum': 0, 'www.': 0, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'dir': 'git-commits-cleaned', 'id': '393123', 'n_tokens_mistral': 755, 'n_tokens_neox': 712, 'n_words': 338}