face-recognition

问题 I have a python function with opencv 3. it works without virtual environment.Also I installed opencv on venv from:pyimagesearch. i am trying to run that python function on venv, then it gives an error : AttributeError: 'module' object has no attribute 'createLBPHFaceRecognizer' without venv in terminal: gkhan@Gkan ~/Masaüstü/face_recognizer $ python face_recognizer.py Yol :./sinif/114.jpg. 114 Yuz Tanindi 12 with venv in terminal: gkhan@Gkan ~/Masaüstü/face_recognizer $ workon cv (cv)gkhan

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 4 years ago . Does anybody know which,currently,is the best library for realizing a real time face-tracking solution for iPhone? I've done a research but I've found quite old articles about OpenCV portings. I would like to know if there is any specific,reliable,fast (and possibly free) AR solution for overlay in real time an

问题 Closed. This question is off-topic. It is not currently accepting answers. Want to improve this question? Update the question so it's on-topic for Stack Overflow. Closed 5 years ago . Are there any face recognition algorithms written in the R statistical language? If not, please provide guidance on where I might start translating other algorithms to R. 回答1: Be sure to check out the update made on May 8, 2013. See below. Here are a few links/thoughts to get you started: Does it have to be in R

问题 I have a very large photo gallery with thousands of similar people, objects, locations, things. The majority of the people in the photos have their own user accounts and avatar photos to match. There are also logical short lists of people potentially in the photo based on additional data available for each photo. I allow users to tag photos with their friends and people they know but an automated process would be better. I've used photo tagger/finder from face.com integrating with Facebook

问题 Dlib C++ can detect landmark and estimate face pose very well. However, how can I get 3D coordinate Axes direction (x,y,z) of head pose? 回答1: I was also facing the same issue, a while back ago, searched and found 1-2 useful blog posts, this link would get you an overview of the techniques involved, If you only need to calculate the 3D pose in decimal places then you may skip the OpenGL rendering part, However if you want to visually get the Feedback then you may try with OpenGL as well, But I

问题 I am trying to make face recognition by Principal Component Analysis (PCA) using python. Now I am able to get the minimum euclidean distance between the training images images and the input image input_image . Here is my code: import os from PIL import Image import numpy as np import glob import numpy.linalg as linalg #Step1: put database images into a 2D array filenames = glob.glob('C:\\Users\\me\\Downloads\\/*.pgm') filenames.sort() img = [Image.open(fn).convert('L').resize((90, 90)) for fn

问题 RuntimeError: CMake must be installed to build the following extensions: dlib Failed building wheel for dlib Running setup.py clean for dlib Failed to build dlib 回答1: I ran into this issue as well. I am using windows and have a python environment that I am installing the requirements to. I ran pip install cmake , and then pip install dlib . I no longer received the error and successfully installed dlib. 回答2: I also had the same issue. For those who deals with it now - Firstly you have to

问题 I am looking for already trained haarcascades of facial fiducial points (left corner of left eye, right corner of left eye, left corner of right eye, right corner of right eye, left corner of mouth, right corner of mouth, left, center and right side of nose). Does anyone know where can I download an already trained haarcascades to use with OpenCV's VJ function? 回答1: If I m not so badly mistaken, HaarCascade works with objects not with specific points. There are already classifiers for nose

问题 I was working on Face Recognition project. After training the database and calling EigenObjectRecognizer, the result is a black image with unrecognized label.When the code runs, it looks like the following http://www.mediafire.com/view/?ewns4iqvd51adsc .And as shown in the picture the detected and supposed to be recognized and extracted face in the image box is totally black. And the input image for recognition is exactly the same as the one the database is trained with.So why it has kept

问题 I'm trying develop a facial recognition system. But the issue is it can be by-passed by a photo. I'm using google vision api to detect faces. Is there a way to avoid detecting faces in a photo? Just want to know if there is a real person standing in front of the camera. 回答1: The Google Vision API does not support distinguishing between a real face and a face in a photo. There are a number of ways that you might try to do this in general. Perhaps the most reliable way would be to use stereo