Major slowdown for evaluating edges in current main

[bentaculum]

• traccuracy version: main branch vs f8c982c57b8aa92ac8ab5410318ad2b20c0c6f76
• Python version: 3.10.13
• Operating System: Ubuntu 22.04

Description

The recent changes are considerably slowing down the evaluation of FP/FN edges. For the example below, one of the phase contrast datasets from the CTC, I get an estimate of 01:45h. With commit f8c982c57b8aa92ac8ab5410318ad2b20c0c6f76, which I was using until just now, this evaluation gets done in only seconds.

What I Did

I slightly adapted the example, to simply compare GT vs GT of a slightly larger CTC dataset:

import os
from pathlib import Path
import pprint
import urllib.request
import zipfile

from tqdm import tqdm

from traccuracy import run_metrics
from traccuracy.loaders import load_ctc_data
from traccuracy.matchers import CTCMatched, IOUMatched
from traccuracy.metrics import CTCMetrics, DivisionMetrics

pp = pprint.PrettyPrinter(indent=4)

url = "http://data.celltrackingchallenge.net/training-datasets/PhC-C2DL-PSC.zip"
data_dir = "downloads"

if not os.path.exists(data_dir):
    os.mkdir(data_dir)

filename = url.split("/")[-1]
file_path = os.path.join(data_dir, filename)
ds_name = filename.split(".")[0]

# Add a utility to make a progress bar when downloading the file
class DownloadProgressBar(tqdm):
    def update_to(self, b=1, bsize=1, tsize=None):
        if tsize is not None:
            self.total = tsize
        self.update(b * bsize - self.n)


if not os.path.exists(file_path):
    print(f"Downloading {ds_name} data from the CTC website")
    # Downloading data
    with DownloadProgressBar(
        unit="B", unit_scale=True, miniters=1, desc=url.split("/")[-1]
    ) as t:
        urllib.request.urlretrieve(url, file_path, reporthook=t.update_to)
    # Unzip the data
    # TODO add a progress bar to zip as well
    with zipfile.ZipFile(file_path, "r") as zip_ref:
        zip_ref.extractall(data_dir)


gt_data = load_ctc_data(
    "downloads/PhC-C2DL-PSC/01_GT/TRA", "downloads/PhC-C2DL-PSC/01_GT/TRA/man_track.txt"
)
pred_data = load_ctc_data(
    "downloads/PhC-C2DL-PSC/01_GT/TRA", "downloads/PhC-C2DL-PSC/01_GT/TRA/man_track.txt"
)

ctc_results = run_metrics(gt_data=gt_data, pred_data=pred_data, matcher=CTCMatched, metrics=[CTCMetrics, DivisionMetrics],)
pp.pprint(ctc_results)

[bentaculum]

I am proposing a solution in #59.

[bentaculum]

Solved and merged in #59, closing.