face-detection

问题 I am using the inbuilt cascade classifier for the face detection. This is how the code is (OpenCV Python Tutorials): import numpy as np import cv2 face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') img = cv2.imread('ammma.jpg') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.3, 5) for (x,y,w,h) in faces: cv2.Rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) roi_gray = gray[y

问题 I am using the inbuilt cascade classifier for the face detection. This is how the code is (OpenCV Python Tutorials): import numpy as np import cv2 face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_default.xml') eye_cascade = cv2.CascadeClassifier('haarcascade_eye.xml') img = cv2.imread('ammma.jpg') gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY) faces = face_cascade.detectMultiScale(gray, 1.3, 5) for (x,y,w,h) in faces: cv2.Rectangle(img,(x,y),(x+w,y+h),(255,0,0),2) roi_gray = gray[y

问题 I am currently using google cloud-vision api for a project. I want to assign a unique ID to a face, so that it automatically detects which IDs any image contains. This way I can know which person is in the image. Can cloud-vision distinguish faces and return some unique ID for a face? 回答1: NO , and as Armin has already mentioned, Google Vision API doesn't support Facial Recognition or Face verification. It only performs face detection on an image. What you can actually do is to use tensorflow

问题 i've tried to detect faces from my webcam , but it was only detect the first face which appeared in the first frame , then it will crush , i have used mtcnn to detection operation import cv2 i = 0 capture = cv2.VideoCapture(0) while(True): ret, frame = capture.read() frames_tracked = [] print('\rTracking frame: {}'.format(i + 1), end='') frame_pil = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB) frame_pil = Image.fromarray(frame_pil) boxes,_ = mtcnn.detect(frame_pil) frame_draw = frame_pil.copy() draw

问题 i've tried to detect faces from my webcam , but it was only detect the first face which appeared in the first frame , then it will crush , i have used mtcnn to detection operation import cv2 i = 0 capture = cv2.VideoCapture(0) while(True): ret, frame = capture.read() frames_tracked = [] print('\rTracking frame: {}'.format(i + 1), end='') frame_pil = cv2.cvtColor(frame,cv2.COLOR_BGR2RGB) frame_pil = Image.fromarray(frame_pil) boxes,_ = mtcnn.detect(frame_pil) frame_draw = frame_pil.copy() draw

问题 I'm trying to outline the whole image with a path so I could crop it out, but the path is not following the face's outline. Here's my code : for (Landmark landmark : face.getLandmarks()) { if (face.getLandmarks().indexOf(landmark) == 0) { path.moveTo(landmark.getPosition().x, landmark.getPosition().y); } else { path.lineTo(landmark.getPosition().x, landmark.getPosition().y); } } How do I make it so that the path only follows the outer outline of the face 回答1: Look at the Type of each landmark

问题 Summary: Our app depends on a high detection speed of facial landmarks (= like eyes open or closed). Thus I developed an algorythm that takes the position of the face from the last frame and crops the image from the next frame. This works perfectly and the Face Detector only has to process a quarter of the image. But it does not increase the detection speed. Does anybody know why? Edit: All that my algorythm is doing is croping the image based on the information from the last image. But it

问题 How can I do a basic face alignment on a 2-dimensional image with the assumption that I have the position/coordinates of the mouth and eyes. Is there any algorithm that I could implement to correct the face alignment on images? 回答1: Face (or image) alignment refers to aligning one image (or face in your case) with respect to another (or a reference image/face). It is also referred to as image registration. You can do that using either appearance ( intensity-based registration ) or key-point

问题 Firstly, I am sorry if the title is long. I am working on face detection using python. I am trying to write a script where it will notify user when there is same picture or almost same picture/faces detected between two directories/folder. Below is the script that I wrote so far. import cv2 import glob, requests def detect1(): face_cascade = cv2.CascadeClassifier('haarcascade_frontalface_alt.xml') for img in glob.glob('/Users/Ling/Pythonfiles/Faces/*.jpg'): cv_img = cv2.imread(img) gray = cv2

问题 I would like to perform face detection / tracking on a video file (e.g. an MP4 from the users gallery) using the Android Vision FaceDetector API. I can see many examples on using the CameraSource class to perform face tracking on the stream coming directly from the camera (e.g. on the android-vision github), but nothing on video files. I tried looking at the source code for CameraSource through Android Studio, but it is obfuscated, and I couldn't see the original online. I image there are