Comments (8)
it worked for me
from retinaface.
if you set the threshold to a lower value, then it will find faces easily.
https://github.com/serengil/retinaface/blob/master/retinaface/RetinaFace.py#L210
from retinaface.
@serengil Could you share what values you used? I tried lowering it:
faces = RetinaFace.extract_faces(img_path = "test.jpg", align = True, threshold=0.01)
But I'm still getting an empty array. Not sure if it makes a difference, but I'm not using CUDA to do any calculations:
Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
Ignore above cudart dlerror if you do not have a GPU set up on your machine.
And I'm using a clean install of deepface, current build using pip install -e .
from retinaface.
I used the default one. You can find the result in the attachment.
from retinaface import RetinaFace
import matplotlib.pyplot as plt
img_path = "x.jpg"
faces = RetinaFace.extract_faces(img_path = img_path, align = True)
for face in faces:
plt.imshow(face)
plt.show()
which version are you using? this is mine
(base) sefik@L-GCCDXDDT:~/workspace/facial-recognition-benchmarks-main$ pip show retina-face
Name: retina-face
Version: 0.0.13
from retinaface.
This is what I have:
Name: retina-face
Version: 0.0.15
This is my pip freeze:
absl-py==2.1.0
astunparse==1.6.3
beautifulsoup4==4.12.3
blinker==1.7.0
cachetools==5.3.3
certifi==2024.2.2
charset-normalizer==3.3.2
click==8.1.7
colorama==0.4.6
contourpy==1.2.0
cycler==0.12.1
# Editable install with no version control (deepface==0.0.90)
-e c:\my programs\python projects\phototest\deepface-master
filelock==3.13.3
fire==0.6.0
Flask==3.0.2
flatbuffers==1.12
fonttools==4.50.0
gast==0.4.0
gdown==5.1.0
google-auth==2.29.0
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
grpcio==1.62.1
gunicorn==21.2.0
h5py==3.10.0
idna==3.6
importlib_metadata==7.1.0
importlib_resources==6.4.0
itsdangerous==2.1.2
Jinja2==3.1.3
keras==2.9.0
Keras-Preprocessing==1.1.2
kiwisolver==1.4.5
libclang==18.1.1
Markdown==3.6
MarkupSafe==2.1.5
matplotlib==3.8.3
mtcnn==0.1.1
numpy==1.22.3
oauthlib==3.2.2
opencv-python==4.9.0.80
opt-einsum==3.3.0
packaging==24.0
pandas==2.0.3
Pillow==9.0.0
protobuf==3.19.6
pyasn1==0.6.0
pyasn1_modules==0.4.0
pyparsing==3.1.2
PySocks==1.7.1
python-dateutil==2.9.0.post0
pytz==2024.1
requests==2.31.0
requests-oauthlib==2.0.0
retina-face==0.0.15
rsa==4.9
six==1.16.0
soupsieve==2.5
tensorboard==2.9.1
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow==2.9.0
tensorflow-estimator==2.9.0
tensorflow-io-gcs-filesystem==0.31.0
termcolor==2.4.0
tqdm==4.66.2
typing_extensions==4.10.0
tzdata==2024.1
urllib3==2.2.1
Werkzeug==3.0.1
wrapt==1.16.0
zipp==3.18.1
from retinaface.
Okay I get the same error when upgrade to 15.
from retinaface.
This is a bug. You can downgrade this to 13 not to have that error. Hope to sort this soon.
from retinaface.
Closed with PR - #100
from retinaface.
Related Issues (20)
- The retina face is too slow on a card with Arm64 Mali GPU. HOT 1
- High VRAM usage on Linux HOT 2
- Which library versions do you suggest for maximum GPU performance on Windows? HOT 1
- add github actions and perform unit tests & linting HOT 1
- create a logger HOT 1
- expanding facial area with percentage HOT 1
- Adding requirements and readme as a data file HOT 1
- Retina-face forces the installation of full tensorflow, even when tensorflow-cpu is already installed HOT 2
- Bug while feeding input image argument from web HOT 1
- do not limit align first detect second with one face HOT 1
- facial area variables HOT 1
- Error: keras to tf HOT 5
- Can detect_faces take in batched inputs? as in several rgb arrays at a time? HOT 1
- Argument `padding` must be either 'valid' or 'same'. Received: padding=VALID HOT 2
- publish a release on pip not to have `Argument padding must be either 'valid' or 'same'. Received: padding=VALID`
- Error when using retinaface with the latest TensorFlow version (2.16.1) HOT 6
- alignment_procedure crashes when both eyes are in the same position HOT 9
- detect_faces image preprocessing? HOT 2
- A KerasTensor cannot be used as input to a TensorFlow function HOT 4
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from retinaface.