image_path = "/mnt/sda2/face_dataset/VN-celeb/855/8.png"
SF = SimilarityFinder()
DB = Database()
images_folder = Config.dataset_folder
images_subfolders = glob.glob(os.path.join(images_folder, "*"))
positive = 0
batch_subfolders = images_subfolders[1:800]
for index, subfolder in enumerate(batch_subfolders):
images = glob.glob(os.path.join(subfolder, "*"))
image = images[-1]
print(image)
try:
response = SF.find_similar(image)
predicted_persistedFaceId = response[0]["persistedFaceId"]
predicted_faceId = DB.find_FaceId(predicted_persistedFaceId)
gt_faceId = image.split("/")[-2]
if gt_faceId == predicted_faceId:
positive += 1
else:
print("{}./ Image : {}\n\tgroudtruth : {}, predicted : {}".
format(index, image, gt_faceId, predicted_faceId))
except Exception as e:
print(e)
time.sleep(60)
try:
response = SF.find_similar(image)
predicted_persistedFaceId = response[0]["persistedFaceId"]
predicted_faceId = DB.find_FaceId(predicted_persistedFaceId)
gt_faceId = image.split("/")[-2]
if gt_faceId == predicted_faceId:
