machine-learning-deep-learning/Machine-Learning-Collection
1
0
Fork 0
mirror of https://github.com/aladdinpersson/Machine-Learning-Collection.git synced 2026-02-20 13:50:41 +00:00
Code Issues Packages Projects Releases Wiki Activity

Initial commit

Browse Source
This commit is contained in:
Aladdin Persson
2021-01-30 21:49:15 +01:00
commit 65b8c80495
432 changed files with 1290844 additions and 0 deletions
Download Patch File Download Diff File Expand all files Collapse all files

115
ML_tests/Object_detection_tests/map_test.py Executable file
View File

@@ -0,0 +1,115 @@
import sys
import unittest
import torch
sys.path.append("ML/Pytorch/object_detection/metrics/")
from mean_avg_precision import mean_average_precision
class TestMeanAveragePrecision(unittest.TestCase):
def setUp(self):
# test cases we want to run
self.t1_preds = [
[0, 0, 0.9, 0.55, 0.2, 0.3, 0.2],
[0, 0, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 0, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t1_targets = [
[0, 0, 0.9, 0.55, 0.2, 0.3, 0.2],
[0, 0, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 0, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t1_correct_mAP = 1
self.t2_preds = [
[1, 0, 0.9, 0.55, 0.2, 0.3, 0.2],
[0, 0, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 0, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t2_targets = [
[1, 0, 0.9, 0.55, 0.2, 0.3, 0.2],
[0, 0, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 0, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t2_correct_mAP = 1
self.t3_preds = [
[0, 1, 0.9, 0.55, 0.2, 0.3, 0.2],
[0, 1, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 1, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t3_targets = [
[0, 0, 0.9, 0.55, 0.2, 0.3, 0.2],
[0, 0, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 0, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t3_correct_mAP = 0
self.t4_preds = [
[0, 0, 0.9, 0.15, 0.25, 0.1, 0.1],
[0, 0, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 0, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t4_targets = [
[0, 0, 0.9, 0.55, 0.2, 0.3, 0.2],
[0, 0, 0.8, 0.35, 0.6, 0.3, 0.2],
[0, 0, 0.7, 0.8, 0.7, 0.2, 0.2],
]
self.t4_correct_mAP = 5 / 18
self.epsilon = 1e-4
def test_all_correct_one_class(self):
mean_avg_prec = mean_average_precision(
self.t1_preds,
self.t1_targets,
iou_threshold=0.5,
box_format="midpoint",
num_classes=1,
)
self.assertTrue(abs(self.t1_correct_mAP - mean_avg_prec) < self.epsilon)
def test_all_correct_batch(self):
mean_avg_prec = mean_average_precision(
self.t2_preds,
self.t2_targets,
iou_threshold=0.5,
box_format="midpoint",
num_classes=1,
)
self.assertTrue(abs(self.t2_correct_mAP - mean_avg_prec) < self.epsilon)
def test_all_wrong_class(self):
mean_avg_prec = mean_average_precision(
self.t3_preds,
self.t3_targets,
iou_threshold=0.5,
box_format="midpoint",
num_classes=2,
)
self.assertTrue(abs(self.t3_correct_mAP - mean_avg_prec) < self.epsilon)
def test_one_inaccurate_box(self):
mean_avg_prec = mean_average_precision(
self.t4_preds,
self.t4_targets,
iou_threshold=0.5,
box_format="midpoint",
num_classes=1,
)
self.assertTrue(abs(self.t4_correct_mAP - mean_avg_prec) < self.epsilon)
def test_all_wrong_class(self):
mean_avg_prec = mean_average_precision(
self.t3_preds,
self.t3_targets,
iou_threshold=0.5,
box_format="midpoint",
num_classes=2,
)
self.assertTrue(abs(self.t3_correct_mAP - mean_avg_prec) < self.epsilon)
if __name__ == "__main__":
print("Running Mean Average Precisions Tests:")
unittest.main()