File size: 2,243 Bytes
4a95d4d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 | from unittest.mock import patch
import numpy as np
import pandas as pd
import signature_verification.constants as cons
from signature_verification.evaluate import (
compute_accuracy_roc,
gen_data,
process_test_metadata,
)
def test_process_test_metadata(tmpdir):
# Create a fake test data csv
path = tmpdir.join("fake_test_data.csv")
fake_csv_data = pd.DataFrame(
[
"./CEDAR/38/original_38_13.png,./CEDAR/38/forgeries_38_20.png,0",
"./CEDAR/12/original_12_22.png,./CEDAR/12/forgeries_12_14.png,0",
"./CEDAR/33/original_33_10.png,./CEDAR/33/forgeries_33_24.png,0",
]
)
csv_data = fake_csv_data[0].str.split(",", expand=True)
csv_data.to_csv(path, index=False, header=False)
pairs_data, labels_list = process_test_metadata(path)
expected_pairs_data = [
("./CEDAR/38/original_38_13.png", "./CEDAR/38/forgeries_38_20.png"),
("./CEDAR/12/original_12_22.png", "./CEDAR/12/forgeries_12_14.png"),
("./CEDAR/33/original_33_10.png", "./CEDAR/33/forgeries_33_24.png"),
]
expected_labels_list = [0, 0, 0]
assert pairs_data == expected_pairs_data
assert labels_list == expected_labels_list
def test_compute_accuracy_roc():
# Create a fake result of model predictions
predictions = np.array(
[0.89941, 0.234, 0.5543, 0.7543, 1.245, 2.54687, 0.441247, 1.1215, 2.3333]
)
labels = np.array([1, 1, 1, 1, 1, 0, 0, 0, 0])
max_acc, best_thresh = compute_accuracy_roc(predictions, labels)
# Check the range of accuracy and threshold
assert 0.0 <= max_acc <= 1.0
assert 0.234 <= best_thresh <= 2.54687
def create_cv2_imread(filepath, flags):
return np.ones((cons.IMG_H, cons.IMG_W), dtype=np.uint8) * 255
def test_gen_data():
with patch("cv2.imread", side_effect=create_cv2_imread):
batch_size = 2
actual_gen = gen_data(batch_size=batch_size)
pairs, targets = next(actual_gen)
assert pairs[0].shape == (batch_size, cons.IMG_H, cons.IMG_W, 1)
assert pairs[1].shape == (batch_size, cons.IMG_H, cons.IMG_W, 1)
assert targets.shape == (batch_size,)
|