def test_bias_dataframe():
"Make sure the data is loaded properly"
fname = DATADIR.joinpath("bfw-datatable.pkl")
data = load_bfw_datatable(fname)
assert len(data) == 923898
npt.assert_allclose(data["score"].mean(), 0.5864211374778945)
import numpy as np
import facebias.utils as futils
from facebias.iotools import load_bfw_datatable
version = "0.1.5"
dir_data = "../../data/bfw/meta/"
f_datatable = f"{dir_data}bfw-v{version}-datatable.pkl"
thresholds = np.linspace(0.15, 0.6, 1000)
data = load_bfw_datatable(f_datatable, default_score_col="sphereface")
# reorder for find_best_threshold(s
data = data.loc[data.a1 == data.a2]
# data = data[["p1", "p2", "score", "label", "fold"]]
global_threshold, _ = futils.find_best_threshold(
thresholds, data[["p1", "p2", "score", "label", "fold"]])
running_scores = []
data["y1"] = (data["score"] > global_threshold).values.astype(int)
data.fold = data.fold.astype(int)
folds = data.fold.unique()
for k in folds:
# for each fold
df_test = data.loc[data.fold == k]
y_pred = df_test["y1"]
y_true = df_test["label"].values.astype(int)
running_scores.append(sum((y_pred == y_true).astype(int)) / len(y_pred))
print(running_scores[-1])
print(np.mean(running_scores))
import numpy as np
import pandas as pd
from facebias.utils import add_package_path
from sklearn.metrics import confusion_matrix, roc_curve
# add_package_path()
from facebias.iotools import load_bfw_datatable
global_threshold = 0.6
dir_data = "../../data/"
dir_features = f"{dir_data}features/senet50/"
f_datatable = f"{dir_data}bfw-datatable.pkl"
data = load_bfw_datatable(f_datatable, default_score_col="senet50")
data["yp0"] = (data["score"] > global_threshold).astype(int)
fpath = f"{dir_data}/interm/thresholds.pkl"
threholds = pd.read_pickle(fpath)
threholds.optimal_threshold = threholds.loc[
threholds.optimal_threshold is None, "optimal_threshold"
] = global_threshold
data["yp3"] = (data["score"] > threholds["optimal_threshold"]).astype(int)
target_far_values = np.array([0.3, 0.1, 0.01, 0.001, 0.0001])
tags = (
r"\textbf{\gls{af}}",
r"\textbf{\gls{am}}",
r"\textbf{\gls{bf}}",