from face_recognition import FaceRecognition
import base64
from io import BytesIO
data = {
'data':
'data:image/jpeg;base64,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'
}
# with open("1.jpg", "rb") as image_file:
# encoded_string = base64.b64encode(image_file.read())
# encoded_string = str(encoded_string, encoding='utf-8')
# print(encoded_string)
#
# model = FaceRecognition()
# model.predict(encoded_string)
encoded_string = data.get('data')
encoded_string = encoded_string.split(',')[1]
model = FaceRecognition()
model.predict(encoded_string)
import cv2
from mtcnn import MTCNN
from face_recognition import FaceRecognition
detector = MTCNN()
fr = FaceRecognition()
image = cv2.cvtColor(cv2.imread("test.png"), cv2.COLOR_BGR2RGB)
print(fr.predict(image))
exit()
result = detector.detect_faces(image)
# Result is an array with all the bounding boxes detected. We know that for 'ivan.jpg' there is only one.
bounding_box = result[0]['box']
keypoints = result[0]['keypoints']
cv2.rectangle(
image, (bounding_box[0], bounding_box[1]),
(bounding_box[0] + bounding_box[2], bounding_box[1] + bounding_box[3]),
(0, 155, 255), 2)
bounding_box = result[1]['box']
cv2.rectangle(
image, (bounding_box[0], bounding_box[1]),
(bounding_box[0] + bounding_box[2], bounding_box[1] + bounding_box[3]),
(0, 155, 255), 2)
bounding_box = result[2]['box']
cv2.rectangle(
