deepface | Lightweight Face Recognition and Facial Attribute Analysis | Computer Vision library
kandi X-RAY | deepface Summary
kandi X-RAY | deepface Summary
Deepface is a lightweight face recognition and facial attribute analysis (age, gender, emotion and race) framework for python. It is a hybrid face recognition framework wrapping state-of-the-art models: VGG-Face, Google FaceNet, OpenFace, Facebook DeepFace, DeepID, ArcFace and Dlib. Those models already reached and passed the human level accuracy. The library is mainly based on TensorFlow and Keras.
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Top functions reviewed by kandi - BETA
- Inception ResNet v2 .
- Calculate face analysis .
- Finds a VGG - based model using a given model .
- Analyze model .
- Verify two images .
- Preprocess the input image .
- Verify a VGG - compatible wrapper .
- Detect the face of a given image .
- representation function
- Represent an image .
deepface Key Features
deepface Examples and Code Snippets
Lines of Code : 29License : Permissive (MIT)
Copypip install retina-face
from retinaface import RetinaFace
resp = RetinaFace.detect_faces("img1.jpg")
{
"face_1": {
"score": 0.9993440508842468,
"facial_area": [155, 81, 434, 443],
"landmarks": {
"right_eye": [2 results = DeepFace.verify(np.array(PILIMAGE), ...)
picture= "extracted_face_picture/single_face_picture.jpg"
picture= Image.open(picture)
.
.
df.verify(picture, np.array(frame), "Facenet")
df.verify(np.array(picture),np.array(frame), "Facenet")
Predictions = torch.argmax(Pred)
Predictions = torch.argmax(Pred).item()
for i in range(0, len(idendities) - 1):
for j in range(i + 1, len(idendities)):
cross_product = itertools.product(samples_list[i], samples_list[j])
cross_product = list(cross_product)
for cross_sample in cross_for i in range(len(idendities) - 1):
for j in range(i + 1, len(idendities)):
for cross_sample in itertools.product(samples_list[i], samples_list[j]):
# do something ...
import csv
for i in ry_test = y_test.astype(int)
from sklearn.metrics import confusion_matrix, accuracy_score, roc_auc_score, roc_curve
y_pred_proba = predictions[::, 1]
y_test = y_test.astype(int)
fpr, tpr, _ = roc_curve(y_test, y_#!pip install deepface
from deepface import DeepFace
detectors = ['opencv', 'ssd', 'mtcnn', 'dlib']
img = DeepFace.detectFace("img.jpg", detector_backend = detectors[0])
!wget "http://*.jpg" -O "1.jpg"
!wget "https://*.jpg" -O "2.jpg"
import cv2
from google.colab.patches import cv2_imshow
im1 = cv2.imread("1.jpg")
#cv2.imshow("img", im1)
cv2_imshow(im1)
from sklearn.datasets import fetch_lfw_pairs
fetch_lfw_pairs = fetch_lfw_pairs(subset = 'test', color = True, resize = 1)
pairs = fetch_lfw_pairs.pairs
labels = fetch_lfw_pairs.target
predictions = []
for i in rangCommunity Discussions
Trending Discussions on deepface
QUESTION
I'm trying to detect multiple faces in a picture using the deepface library with dlib as the backend detector. I'm using the DlibWrapper.py from the deeepface library and i have the following issue: In some cases, the detector returns the bounding box coordinates but doesn't return the detected face image detected face-box coordinates.
I was wondering if this bug occurs because of the negative values of some coordinates of the bounding boxes but i figured out that was not the case, as the negative values are features, not bugs. Here is the DlibWrapper from the deepface library.
...ANSWER
Answered 2022-Jan-18 at 13:43Solved!There are edge cases where original rectangle is partially outside the image window. That happens with dlib. So, instead of
- detected_face = img[top:bottom, left:right],
the detected face should be
- detected_face = img[max(0, top): min(bottom, img_height), max(0, left): min(right, img_width)]
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
ANSWER
Answered 2021-Jul-11 at 22:42Change y - second value in (50,50), (40,50), (30,50) - ie. (50,50), (50,80), (50,110)
Minimal working code
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
Hello StackOverFlow Team: I built a model based on (Vgg_Face_Model) with weights loaded (vgg_face_weights.h5). Note that I use tensorflow-gpu = 2.1.0 , and keras=2.3.1 , with Anaconda 3 create it as interpreter and used with pycharm But the code shows an error in the part :
...ANSWER
Answered 2021-May-24 at 09:55from tensorflow.python.keras.backend import set_session
sess = tf.Session()
#This is a global session and graph
graph = tf.get_default_graph()
set_session(sess)
#now where you are calling the model
global sess
global graph
with graph.as_default():
set_session(sess)
input_descriptor = [model.predict(face), img]
QUESTION
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 developed a code by following a non-complete tutorial for emotion recognition with using PyTorch. I had so many errors but i fixed them thanks to the other questions here. But i simply stucked at this one. I am running my code, then my webcam opens but i see "Neutral" emotions all the time, even tough i perform different emotions. But on the console i am seeing other emotions as recorded, like:
...ANSWER
Answered 2021-Mar-19 at 12:34Predictions is a tensor, so you need its value and not the tensor itself.
Change this line:
QUESTION
I am changing pandas into cudf to make faster aggregating and reduce the processing speed. I figure out one library which works on GPU with pandas.
"CUDF LINK" https://github.com/rapidsai/cudf
When I entered the below to install in my project it gives an error and I also tried many version of numba.
...ANSWER
Answered 2021-Feb-04 at 13:35When trying to install cuDF 0.13, conda is apparently finding a numba version that is incompatible with that cuDF 0.13.
cuDF 0.13 is out of date. The current stable release is 0.17 and the nightly is 0.18. We'll update the README, as it should provide installation instructions for the current version.
We recommend creating a fresh conda environment. Please try the following conda install command, found here:
QUESTION
The identities list contains a big array of approximately 57000 images. Now, I am creating a negative list with the help of itertools.product(). This stores the whole list in memory which is very costly and my system hanged after 4 minutes.
How can I optimize the below code and avoid saving in memory?`
...ANSWER
Answered 2021-Feb-02 at 05:59The product from itertools is a generator so naturally it dose not store the whole list in memory, but in the next line, cross_product = list(cross_product) you convert it to list object which store the whole data in your memory.
The idea of a generator is that you don't do all the calculation at the same time, as you do with your call list(itertools.product(samples_list[i], samples_list[j])). So what you want to do is generate the results one by one:
Try something like this:
QUESTION
I have just updated python version from 3.5 to 3.7 and getting an error in constructing ROC curve. I did not change anything in code but it gives some unknown error
Code
...ANSWER
Answered 2020-Dec-31 at 13:53if we print the value of type_of_target(y_test) the output value is "unknown". Now, we have to change the unknown to integer. So we will do like this
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