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Commit 73171120 authored by Tiago de Freitas Pereira's avatar Tiago de Freitas Pereira
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Merge branch '87-no-way-of-plotting-open-set-dir-curves' into 'master'

Resolve "No way of plotting open-set DIR curves"

Closes #87

See merge request !94
parents f8970c90 70e39528
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1 merge request!94Resolve "No way of plotting open-set DIR curves"
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......@@ -47,6 +47,7 @@ def command_line_arguments(command_line_parameters):
parser.add_argument('-m', '--mindcf', action = 'store_true', help = "If given, minDCF will be computed.")
parser.add_argument('--cost', default=0.99, help='Cost for FAR in minDCF')
parser.add_argument('-r', '--rr', action = 'store_true', help = "If given, the Recognition Rate will be computed.")
parser.add_argument('-o', '--rank', type=int, default=1, help = "The rank for which to plot the DIR curve")
parser.add_argument('-t', '--thresholds', type=float, nargs='+', help = "If given, the Recognition Rate will incorporate an Open Set handling, rejecting all scores that are below the given threshold; when multiple thresholds are given, they are applied in the same order as the --dev-files.")
parser.add_argument('-l', '--legends', nargs='+', help = "A list of legend strings used for ROC, CMC and DET plots; if given, must be the same number than --dev-files.")
parser.add_argument('-F', '--legend-font-size', type=int, default=10, help = "Set the font size of the legends.")
......@@ -55,6 +56,7 @@ def command_line_arguments(command_line_parameters):
parser.add_argument('-R', '--roc', help = "If given, ROC curves will be plotted into the given pdf file.")
parser.add_argument('-D', '--det', help = "If given, DET curves will be plotted into the given pdf file.")
parser.add_argument('-C', '--cmc', help = "If given, CMC curves will be plotted into the given pdf file.")
parser.add_argument('-O', '--dir', help = "If given, DIR curves will be plotted into the given pdf file; This is an open-set measure, which cannot be applied to closed set score files.")
parser.add_argument('-E', '--epc', help = "If given, EPC curves will be plotted into the given pdf file. For this plot --eval-files is mandatory.")
parser.add_argument('-M', '--min-far-value', type=float, default=1e-4, help = "Select the minimum FAR value used in ROC plots; should be a power of 10.")
parser.add_argument('-L', '--far-line-at', type=float, help = "If given, draw a veritcal line at this FAR value in the ROC plots.")
......@@ -68,8 +70,11 @@ def command_line_arguments(command_line_parameters):
# set verbosity level
bob.core.log.set_verbosity_level(logger, args.verbose)
# some sanity checks:
for f in args.dev_files + (args.eval_files or []):
if not os.path.exists(f):
raise ValueError("The provided score file '%s' does not exist", f)
if args.eval_files is not None and len(args.dev_files) != len(args.eval_files):
logger.error("The number of --dev-files (%d) and --eval-files (%d) are not identical", len(args.dev_files), len(args.eval_files))
......@@ -98,6 +103,14 @@ def command_line_arguments(command_line_parameters):
return args
def _add_far_labels(min_far):
# compute and apply tick marks
ticks = [min_far]
while ticks[-1] < 1.: ticks.append(ticks[-1] * 10.)
pyplot.xticks(ticks)
pyplot.axis([min_far, 1., -0.01, 1.01])
def _plot_roc(frrs, colors, labels, title, fontsize=10, position=None, farfrrs=None):
if position is None: position = 'lower right'
......@@ -116,12 +129,7 @@ def _plot_roc(frrs, colors, labels, title, fontsize=10, position=None, farfrrs=N
else:
pyplot.plot([x[0] for x in farfrrs], [(1.-x[1]) for x in farfrrs], '--', color='black')
# compute and apply tick marks
min_far = frrs[0][0][0]
ticks = [min_far]
while ticks[-1] < 1.: ticks.append(ticks[-1] * 10.)
pyplot.axis([min_far, 1., -0.01, 1.01])
pyplot.xticks(ticks)
_add_far_labels(frrs[0][0][0])
# set label, legend and title
pyplot.xlabel('FMR')
......@@ -185,6 +193,39 @@ def _plot_cmc(cmcs, colors, labels, title, fontsize=10, position=None):
return figure
def _plot_dir(cmc_scores, far_values, rank, colors, labels, title, fontsize=10, position=None):
if position is None: position = 'lower right'
# open new page for current plot
figure = pyplot.figure()
# for each probe, for which no positives exists, get the highest negative
# score; and sort them to compute the FAR thresholds
for i, cmcs in enumerate(cmc_scores):
negatives = sorted(max(neg) for neg, pos in cmcs if (pos is None or not numpy.array(pos).size) and neg is not None)
if not negatives:
raise ValueError("There need to be at least one pair with only negative scores")
# compute thresholds based on FAR values
thresholds = [bob.measure.far_threshold(negatives, [], v, True) for v in far_values]
# compute detection and identification rate based on the thresholds for
# the given rank
rates = [bob.measure.detection_identification_rate(cmcs, t, rank) for t in thresholds]
# plot DIR curve
pyplot.semilogx(far_values, rates, figure=figure, color=colors[i], label=labels[i])
# finalize plot
_add_far_labels(far_values[0])
pyplot.xlabel('FAR')
pyplot.ylabel('DIR')
pyplot.legend(loc=position, prop = {'size':fontsize})
pyplot.title(title)
return figure
def _plot_epc(scores_dev, scores_eval, colors, labels, title, fontsize=10, position=None):
if position is None: position = 'upper center'
# open new page for current plot
......@@ -367,15 +408,14 @@ def main(command_line_parameters=None):
try:
# create a multi-page PDF for the EPC curve
pdf = PdfPages(args.epc)
pdf.savefig(_plot_epc(scores_dev, scores_eval, colors, args.legends, args.title if args.title is not None else "" , args.legend_font_size, args.legend_position), bbox_inches='tight')
pdf.savefig(_plot_epc(scores_dev, scores_eval, colors, args.legends, args.title[0] if args.title is not None else "" , args.legend_font_size, args.legend_position), bbox_inches='tight')
pdf.close()
except RuntimeError as e:
raise RuntimeError("During plotting of EPC curves, the following exception occured:\n%s" % e)
if args.cmc or args.rr:
if args.cmc or args.rr or args.dir:
logger.info("Loading CMC data on the development " + ("and on the evaluation set" if args.eval_files else "set"))
cmcs_dev = [bob.measure.load.cmc(os.path.join(args.directory, f)) for f in args.dev_files]
if args.eval_files:
......@@ -384,7 +424,7 @@ def main(command_line_parameters=None):
if args.cmc:
logger.info("Plotting CMC curves to file '%s'", args.cmc)
try:
# create a multi-page PDF for the ROC curve
# create a multi-page PDF for the CMC curve
pdf = PdfPages(args.cmc)
# create a separate figure for dev and eval
pdf.savefig(_plot_cmc(cmcs_dev, colors, args.legends, args.title[0] if args.title is not None else "CMC curve for development set", args.legend_font_size, args.legend_position), bbox_inches='tight')
......@@ -392,7 +432,7 @@ def main(command_line_parameters=None):
pdf.savefig(_plot_cmc(cmcs_eval, colors, args.legends, args.title[1] if args.title is not None else "CMC curve for evaluation set", args.legend_font_size, args.legend_position), bbox_inches='tight')
pdf.close()
except RuntimeError as e:
raise RuntimeError("During plotting of ROC curves, the following exception occured:\n%s\nUsually this happens when the label contains characters that LaTeX cannot parse." % e)
raise RuntimeError("During plotting of CMC curves, the following exception occured:\n%s\nUsually this happens when the label contains characters that LaTeX cannot parse." % e)
if args.rr:
logger.info("Computing recognition rate on the development " + ("and on the evaluation set" if args.eval_files else "set"))
......@@ -402,3 +442,19 @@ def main(command_line_parameters=None):
if args.eval_files:
rr = bob.measure.recognition_rate(cmcs_eval[i], args.thresholds[i])
print("The Recognition Rate of the development set of '%s' is %2.3f%%" % (args.legends[i], rr * 100.))
if args.dir:
# compute false alarm values to evaluate
min_far = int(math.floor(math.log(args.min_far_value, 10)))
fars = [math.pow(10., i * 0.25) for i in range(min_far * 4, 0)] + [1.]
logger.info("Plotting DIR curves to file '%s'", args.dir)
try:
# create a multi-page PDF for the DIR curve
pdf = PdfPages(args.dir)
# create a separate figure for dev and eval
pdf.savefig(_plot_dir(cmcs_dev, fars, args.rank, colors, args.legends, args.title[0] if args.title is not None else "DIR curve for development set", args.legend_font_size, args.legend_position), bbox_inches='tight')
if args.eval_files:
pdf.savefig(_plot_dir(cmcs_eval, fars, args.rank, colors, args.legends, args.title[1] if args.title is not None else "DIR curve for evaluation set", args.legend_font_size, args.legend_position), bbox_inches='tight')
pdf.close()
except RuntimeError as e:
raise RuntimeError("During plotting of DIR curves, the following exception occured:\n%s")
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......@@ -462,10 +462,10 @@ def test_fusion():
def test_evaluate():
def test_evaluate_closedset():
# tests our 'evaluate' script using the reference files
test_dir = tempfile.mkdtemp(prefix='bobtest_')
reference_files = ('scores-nonorm-dev', 'scores-ztnorm-dev')
reference_files = [os.path.join(data_dir, s) for s in ('scores-nonorm-dev', 'scores-ztnorm-dev')]
plots = [os.path.join(test_dir, '%s.pdf')%f for f in ['roc', 'cmc', 'det', 'epc']]
parameters = [
'--dev-files', reference_files[0], reference_files[1],
......@@ -495,6 +495,32 @@ def test_evaluate():
if os.path.exists(test_dir):
shutil.rmtree(test_dir)
def test_evaluate_openset():
# tests our 'evaluate' script using the reference files
test_dir = tempfile.mkdtemp(prefix='bobtest_')
reference_file = os.path.join(data_dir, 'scores-nonorm-openset-dev')
plot = os.path.join(test_dir, 'dir.pdf')
parameters = [
'--dev-files', reference_file,
'--eval-files', reference_file,
'--directory', os.path.join(data_dir),
'--legends', 'Test',
'--dir', plot,
'--min-far-value', '1e-6',
'-v',
]
# execute the script
from bob.bio.base.script.evaluate import main
try:
main(parameters)
assert os.path.exists(plot)
os.remove(plot)
finally:
if os.path.exists(test_dir):
shutil.rmtree(test_dir)
def test_resources():
......
......@@ -144,7 +144,7 @@ Evaluating Experiments
----------------------
After the experiment has finished successfully, one or more text file containing all the scores are written.
To evaluate the experiment, you can use the generic ``evaluate.py`` script, which has properties for all prevalent evaluation types, such as CMC, ROC and DET plots, as well as computing recognition rates, EER/HTER, Cllr and minDCF.
To evaluate the experiment, you can use the generic ``evaluate.py`` script, which has properties for all prevalent evaluation types, such as CMC, DIR, ROC and DET plots, as well as computing recognition rates, EER/HTER, Cllr and minDCF.
Additionally, a combination of different algorithms can be plotted into the same files.
Just specify all the score files that you want to evaluate using the ``--dev-files`` option, and possible legends for the plots (in the same order) using the ``--legends`` option, and the according plots will be generated.
For example, to create a ROC curve for the experiment above, use:
......
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