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Face Recognition python3 opencv3

Face Recognition python3 opencv3 Face Detector App with opencv3 python3OpenCv Python3 DataSetgenerator : To make a face recognition program, first we need to train the recognizer with dataset of previously captured faces along with its ID, for example we have two person then first person will have ID 1 that s me (yassine) :p and 2nd person will have ID 2 (my binome) :p , so that all the images of person one in the dataset will have ID 1 and all the images of the 2nd person in the dataset will have ID 2, then we will use those dataset images to train the recognizer to predict the 1 of an newly presented face from the live video frame

added by yassine 846347

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Hand Gesture detection

Hand Gesture detection This is cool project based on computer vision tool and it can be created with the help of python and computer vision tool. This is great way to express messages and can be used as a sign language also.

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$13.46
EYE Detection

EYE Detection Easiest way to detect eyes movement  with the help of python and open computer vision tool . , where python is a object oriented language to deliver the best output with the shortest amount of time.

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$95.44
Face Detection

Face Detection Easiest way to detect faces  with the help of python and open computer vision tool . , where python is a object oriented language to deliver the best output with the shortest amount of time.

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$11.29
AI Facial Recognition web system

AI Facial Recognition web system Facial recognition and facial detection web system in Python and Django. Upload images and let the AI find matches for people. With the following project you will be able to: Use it as it is for web facial recognition and facial detection Upload single images or multiple images to build a known faces library Find a match by facial recognition for a single image or multiple files Submit an image for facial detection Browse the results as Web client Access to the database and source code Use the recognition class for other projects Includes pre-trained data (pre-trained data from public libraries , you can also use your own training dataset or another public one) External Sources The model was trained using the following dataset: https://ibug.doc.ic.ac.uk/resources/facial-point-annotations/. How to Use: First, copy the two .dat files from the Part2 zip folder inside the Part1 zip folder (where the manage.py file is).

added by LabAI

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