infer_p3m_portrait_matting

infer_p3m_portrait_matting

About

1.1.1
MIT

Inference of Privacy-Preserving Portrait Matting (P3M)

Task: Image matting
Portrait matting
Privacy-preserving
Semantic segmentation
Trimap
Pytorch

This algorithm proposes inference with Privacy-Preserving Portrait Matting (P3M) model.

Face restoration codeformer

🚀 Use with Ikomia API

1. Install Ikomia API

We strongly recommend using a virtual environment. If you're not sure where to start, we offer a tutorial here.

pip install ikomia

2. Create your workflow

from ikomia.dataprocess.workflow import Workflow
from ikomia.utils.displayIO import display
# Init your workflow
wf = Workflow()

# Add the real_esrgan algorithm
algo = wf.add_task(name = 'infer_p3m_portrait_matting', auto_connect=True)

# Run on your image
wf.run_on(url="https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_portrait.jpg")

# Inspect your results
display(algo.get_input(0).get_image())
display(algo.get_output(1).get_image())

☀️ Use with Ikomia Studio

Ikomia Studio offers a friendly UI with the same features as the API.

  • If you haven't started using Ikomia Studio yet, download and install it from this page.

  • For additional guidance on getting started with Ikomia Studio, check out this blog post.

📝 Set algorithm parameters

  • model_name (str) - default 'resnet34': Name of the model, resnet34 or vitae-s
  • input_size (int) - default: '1024': Size of the input image (stride of 32)
  • method (str) - default: 'HYBRID': Choice of the inference method 'HYBRID' or 'RESIZE'
  • cuda (bool): If True, CUDA-based inference (GPU). If False, run on CPU.
from ikomia.dataprocess.workflow import Workflow
from ikomia.utils.displayIO import display

# Init your workflow
wf = Workflow()

# Add the p3m process to the workflow
algo = wf.add_task(name="infer_p3m_portrait_matting", auto_connect=True)

# Set process parameters
algo.set_parameters({
"model_name" : "resnet34",
"input_size" : "1024",
"method": 'HYBRID',
"cuda" : "True"})

# Run workflow on the image
wf.run_on(url="https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_portrait.jpg")

# Inspect your results
display(algo.get_input(0).get_image())
display(algo.get_output(1).get_image())

🔍 Explore algorithm outputs

Every algorithm produces specific outputs, yet they can be explored them the same way using the Ikomia API. For a more in-depth understanding of managing algorithm outputs, please refer to the documentation.

from ikomia.dataprocess.workflow import Workflow

# Init your workflow
wf = Workflow()

# Add algorithm
algo = wf.add_task(name="infer_p3m_portrait_matting", auto_connect=True)

# Run on your image
wf.run_on(url="https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_portrait.jpg")

# Iterate over outputs
for output in algo.get_outputs():
# Print information
print(output)
# Export it to JSON
output.to_json()

Developer

  • Ikomia
    Ikomia

License

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