All this repository is for learning purposes. I cover here how simple is to remove background from selfie view just like Zoom, Google Meets, Skype, and MS Teams.
- Clone this repository. (don't forget to Star it)
- Install virtual environment:
python -m venv venv - Activate virtual environment:
venv\Scripts\activate - Install all the requirements:
pip install -r requirements.txt - (Optional if have Nvidia GPU): install onnxruntime with GPU support:
pip install onnxruntime-gpu
At this point, when you are looking at this project, I might be already updated this project with more features, but if you want only to run a quick test on your own webcam replace the main.py code with the following:
# main.py
from utils import FPSmetric
from selfieSegmentation import MPSegmentations
from engine import Engine
if __name__ == '__main__':
fpsMetric = FPSmetric()
segmentationModule = MPSegmentations(threshold=0.3, bg_images_path='', bg_blur_ratio=(45, 45))
selfieSegmentation = Engine(webcam_id=0, show=True, custom_objects=[segmentationModule, fpsMetric])
selfieSegmentation.run()You can run it by typing python main.py in a terminal.
# main.py
from utils import FPSmetric
from faceDetection import MPFaceDetection
from engine import Engine
if __name__ == '__main__':
fpsMetric = FPSmetric()
mpFaceDetector = MPFaceDetection()
selfieSegmentation = Engine(webcam_id=0, show=True, custom_objects=[mpFaceDetector, fpsMetric])
selfieSegmentation.run()You can run it by typing python main.py in a terminal.
# main.py
from pencilSketch import PencilSketch
from engine import Engine
if __name__ == '__main__':
pencilSketch = PencilSketch(blur_simga=5)
selfieSegmentation = Engine(image_path='data/porche.jpg', show=True, custom_objects=[pencilSketch])
selfieSegmentation.run()You can run it by typing python main.py in a terminal.
# main.py
from utils import FPSmetric
from engine import Engine
from faceDetection import MPFaceDetection
from faceNet.faceNet import FaceNet
if __name__ == '__main__':
facenet = FaceNet(
detector = MPFaceDetection(),
onnx_model_path = "models/faceNet.onnx",
anchors = "faces",
force_cpu = True,
)
engine = Engine(webcam_id=0, show=True, custom_objects=[facenet, FPSmetric()])
# save first face crop as anchor, otherwise don't use
while not facenet.detect_save_faces(engine.process_webcam(return_frame=True), output_dir="faces"):
continue
engine.run()You can run it by typing python main.py in a terminal.
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