Skip to main content

Packaged version of the Yolov5 facial landmark detector

Project description

pip install y5facegg

Use from Python

Usage
import cv2
from y5facegg import Y5FACE

# set model params
model_path = "y5facegg/weights/yolov5s-face.pt"
device = "cuda:0" # or "cpu"

# init yolov5 model
model = Y5FACE(model_path, device)

# load an image
image_path = 'https://github.com/ultralytics/yolov5/blob/master/data/images/bus.jpg'

# perform inference
bgr_image = cv2.imread(image_path)
res_img = model.predict(bgr_image)
cv2.imwrite('result.jpg', res_img)

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distribution

y5facegg-1.0.1-py36.py37.py38-none-any.whl (93.9 kB view details)

Uploaded Python 3.6 Python 3.7 Python 3.8

File details

Details for the file y5facegg-1.0.1-py36.py37.py38-none-any.whl.

File metadata

  • Download URL: y5facegg-1.0.1-py36.py37.py38-none-any.whl
  • Upload date:
  • Size: 93.9 kB
  • Tags: Python 3.6, Python 3.7, Python 3.8
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.8.0 pkginfo/1.8.2 readme-renderer/34.0 requests/2.27.1 requests-toolbelt/0.9.1 urllib3/1.26.9 tqdm/4.63.1 importlib-metadata/4.8.3 keyring/23.4.1 rfc3986/1.5.0 colorama/0.4.4 CPython/3.6.13

File hashes

Hashes for y5facegg-1.0.1-py36.py37.py38-none-any.whl
Algorithm Hash digest
SHA256 66f6f7f7329b00f051ba032f579c424a13ada1721bd7e621fef645fa521848a3
MD5 9940b70560bd84d2687a783b9d00720c
BLAKE2b-256 ec4b1697f109935ea91262a0d22e1c1176e6884e6fb7fc9ef8bea0f295b4168e

See more details on using hashes here.

Supported by

AWS AWS Cloud computing and Security Sponsor Datadog Datadog Monitoring Fastly Fastly CDN Google Google Download Analytics Microsoft Microsoft PSF Sponsor Pingdom Pingdom Monitoring Sentry Sentry Error logging StatusPage StatusPage Status page