facenet | Face recognition using Tensorflow | Computer Vision library
kandi X-RAY | facenet Summary
kandi X-RAY | facenet Summary
Face recognition using Tensorflow
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Top functions reviewed by kandi - BETA
- Bulk detect face detection
- Create bounding box
- Generate the bounding box for the given image
- Calculate the NMS of boxes
- Train the model
- Get learning rate from file
- Given a set of nrof images return a list of triplets
- Adds summaries for each loss
- Parse command line arguments
- Parse command line arguments
- Load and aligns input images
- Detects the surface of the image
- Validate training set
- Create input pipeline
- Given a list of nrof images return a list of triplets
- Align a list of image data points
- Convolutional convolution layer
- Freeze a graph definition
- Compute face encodings
- Stores the revision info
- Return the model s meta files
- Splits the given dataset into nrof images
- Align an image
- Detects the face of the input image
- Evaluate LFW training
- Performs inception
- Load a VGG model
- Generate inference for images
facenet Key Features
facenet Examples and Code Snippets
from keras_facenet import FaceNet
embedder = FaceNet()
# Gets a detection dict for each face
# in an image. Each one has the bounding box and
# face landmarks (from mtcnn.MTCNN) along with
# the embedding from FaceNet.
detections = embedder.extract(
sudo apt-get install zenity
cd facenet-darknet-inference
#edit makefile
#specify your OPENCV_HEADER_DIR, OPENCV_LIBRARY_DIR, DLIB_HEADER_DIR, DLIB_LIBRARY_DIR, NNPACK_HEADER_DIR, NNPACK_LIBRARY_DIR
make
mkdir data
cd data
touch name
cd ..
mkdir model
@InProceedings{10.1007/978-3-030-29894-4_34,
author="Mougeot, Guillaume and Li, Dewei and Jia, Shuai",
editor="Nayak, Abhaya C. and Sharma, Alok",
title="A Deep Learning Approach for Dog Face Verification and Recognition",
booktitle="PRICAI 2019: Tre
Community Discussions
Trending Discussions on facenet
QUESTION
I am working on a facial comparison app that will give me the closest n number of faces to my target face.
I have done this with dlib/face_recognition as it uses numpy arrays, however i am now trying to do the same thing with facenet/pytorch and running into an issue because it uses tensors.
I have created a database of embeddings and I am giving the function one picture to compare to them. What i would like is for it to sort the list from lowest distances to highest, and give me the lowest 5 results or so.
here is the code I am working on that is doing the comparison. at this point i am feeding it a photo and asking it to compare against the embedding database.
...ANSWER
Answered 2021-Dec-05 at 16:43Unfortunately I cannot test your code, but to me it seems like you are operation on a python list of tuples. You can sort that by using a key:
QUESTION
I'm trying to learn python, for detect someone used mask or not.
when i run this code
...ANSWER
Answered 2021-Nov-26 at 17:44 You have to make sure that files deploy.prototxt
and res10_300x300_ssd_iter_140000.caffemodel
are in the correct directory, then use os.path.join
QUESTION
I have installed a basic python server with deepface library with apache2 on ubuntu.
The library makes a .deepface directory on app initialization but it is unable to do so due to permission denied error as it's hidden in linux by default. I am getting the following error
...ANSWER
Answered 2021-Oct-22 at 10:59You can give permission to that hidden folder by typing sudo chmod 777 -R /var/www/.deepface
.
Make sure cheking the permission by cd /var/www/
and ls -lth
QUESTION
I am following this guide to build an environment to develop an facial recognition project in.
I've pulled the image provided in the guide as shown here using the command
docker pull colemurray/medium-facenet-tutorial
in the Desktop Docker.
I am running a container with the image but I do not understand how I can develop an application in it (e.g having access to the modules downloaded in Docker)
The only action I think I can take here is opening the CLI of the container as shown here but I can't find any guide to use it to add the local folder into the environment.
I understand that using anaconda, I'll just have to activate a environment and run jupyter notebook to develop in that environment and I am trying to do the exact same thing with Docker, but I fail make the same connection, any advice will be greatly appreciated.
...ANSWER
Answered 2021-Aug-14 at 10:37You have three options here:
- Keep the
Dockerfile
in your workdirectory and adding a copy command inDockerfile
that will copy your python files inside docker container. So at the build time your container is built with with the files in it.
QUESTION
My DeepFace Implementation
...ANSWER
Answered 2021-Jun-06 at 10:43If you are using this module, the documentation says:
Herein, face pairs could be exact image paths, numpy array or base64 encoded images
So, presumably, you can make your PIL Images into Numpy arrays like this:
QUESTION
I am using the Facenet algorithm for face recognition. I want to create application based on this, but the problem is the Facenet algorithm returns an array of length 128, which is the face embedding per person.
For person identification, I have to find the Euclidian difference between two persons face embedding, then check that if it is greater than a threshold or not. If it is then the persons are same; if it is less then persons are different.
Let's say If I have to find person x in the database of 10k persons. I have to calculate the difference with each and every person's embeddings, which is not efficient.
Is there any way to store this face embedding efficiently and search for the person with better efficiency?
I guess reading this blog will help the others.
It's in detail and also covers most aspects of implementation.
Face recognition on 330 million faces at 400 images per second
...ANSWER
Answered 2021-May-11 at 05:20Sounds like you want a nearest neighbour search. You could have a look at the various space partitioning data structures like kd-trees
QUESTION
So I've been following this tutorial to detect if person wearing mask or not on camera and got everything to work when using the camera by using the following code:
...ANSWER
Answered 2021-Apr-22 at 10:09the problem is from reading your data from MSS. MSS returns raw pixels in the BGRA form (Blue, Green, Red, Alpha).you can read about it from here. you can convert into BGR via cvtColor:
QUESTION
I am new at tensorflow and models training. I am using the face recognition algorithm based on yolo and facenet. i am now trying to train my own model. But i get an error everytime I do so. I would be very grateful to you if you help me solve it. Thank you in advance. here is the link to the code : https://github.com/AzureWoods/faceRecognition-yolo-facenet/blob/master/train_tripletloss.py
here is t the error:
...ANSWER
Answered 2021-Apr-07 at 03:19QUESTION
I am creating an api that will call a python script using python-shell in nodejs.However when I am running the api,the api returns the error of "Cannot set headers after they have been sent to the client".Below is the code for the api.
...ANSWER
Answered 2021-Mar-22 at 06:29If this if loop get executed a response will be send
QUESTION
I am getting a runtime error that says inputs and weights must be on same. However I made sure that my model and input are on the same device yet I cannot get rid of the error. As far as I read, I know that my input data is not on GPU . Since, In this case image is an input so I tried img = torch.from_numpy(img).to(device)
and pred = model(img)[0].to(device
but no luck. Please let me know what can be done.
Here's the code:
...ANSWER
Answered 2021-Jan-09 at 13:09You need to send the input tensor to your device, not its result:
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