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Readme
MTCNN Face Detector using OpenCV, no reqiurement for tensorflow/pytorch.
pip3 install opencv-python
or pip3 install opencv-python-headless
pip3 install mtcnn-opencv
import cv2
from mtcnn_cv2 import MTCNN
detector = MTCNN()
test_pic = "t.jpg"
image = cv2.cvtColor(cv2.imread(test_pic), cv2.COLOR_BGR2RGB)
result = detector.detect_faces(image)
# Result is an array with all the bounding boxes detected. Show the first.
print(result)
if len(result) > 0:
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)
cv2.circle(image,(keypoints['left_eye']), 2, (0,155,255), 2)
cv2.circle(image,(keypoints['right_eye']), 2, (0,155,255), 2)
cv2.circle(image,(keypoints['nose']), 2, (0,155,255), 2)
cv2.circle(image,(keypoints['mouth_left']), 2, (0,155,255), 2)
cv2.circle(image,(keypoints['mouth_right']), 2, (0,155,255), 2)
cv2.imwrite("result.jpg", cv2.cvtColor(image, cv2.COLOR_RGB2BGR))
# 生成标记了的人脸的图片
with open(test_pic, "rb") as fp:
marked_data = detector.mark_faces(fp.read())
with open("marked.jpg", "wb") as fp:
fp.write(marked_data)
FAQs
MTCNN face detection using OpenCV
We found that mtcnn-opencv demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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