Add the inspireface project to cpp-package.

cpp-package/inspireface/python/test/performance/test_lfw_precision.py

@@ -0,0 +1,59 @@
+from test import *
+import unittest
+import cv2
+
+
+@optional(ENABLE_LFW_PRECISION_TEST, "LFW dataset precision tests have been closed.")
+class LFWPrecisionTestCase(unittest.TestCase):
+
+    def setUp(self) -> None:
+        self.quick = QuickComparison()
+
+    def test_lfw_precision(self):
+        pairs_path = os.path.join(LFW_FUNNELED_DIR_PATH, 'pairs.txt')
+        pairs = read_pairs(pairs_path)
+        self.assertEqual(True, len(pairs) > 0)
+        if os.path.exists(LFW_PREDICT_DATA_CACHE_PATH):
+            print("Loading results from cache")
+            cache = np.load(LFW_PREDICT_DATA_CACHE_PATH, allow_pickle=True)
+            similarities = cache[0]
+            labels = cache[1]
+        else:
+            similarities = []
+            labels = []
+
+            for pair in tqdm(pairs):
+                if len(pair) == 3:
+                    person, img_num1, img_num2 = pair
+                    img_path1 = os.path.join(LFW_FUNNELED_DIR_PATH, person, f"{person}_{img_num1.zfill(4)}.jpg")
+                    img_path2 = os.path.join(LFW_FUNNELED_DIR_PATH, person, f"{person}_{img_num2.zfill(4)}.jpg")
+                    match = True
+                else:
+                    person1, img_num1, person2, img_num2 = pair
+                    img_path1 = os.path.join(LFW_FUNNELED_DIR_PATH, person1, f"{person1}_{img_num1.zfill(4)}.jpg")
+                    img_path2 = os.path.join(LFW_FUNNELED_DIR_PATH, person2, f"{person2}_{img_num2.zfill(4)}.jpg")
+                    match = False
+
+                img1 = cv2.imread(img_path1)
+                img2 = cv2.imread(img_path2)
+
+                if not self.quick.setup(img1, img2):
+                    print("not detect face")
+                    continue
+
+                cosine_similarity = self.quick.comp()
+                similarities.append(cosine_similarity)
+                labels.append(match)
+
+            similarities = np.array(similarities)
+            labels = np.array(labels)
+            # save cache file
+            np.save(LFW_PREDICT_DATA_CACHE_PATH, [similarities, labels])
+
+        # find best threshold
+        best_threshold, best_accuracy = find_best_threshold(similarities, labels)
+        print(f"Best Threshold: {best_threshold:.2f}, Best Accuracy: {best_accuracy:.3f}")
+
+
+if __name__ == '__main__':
+    unittest.main()