infer_p3m_portrait_matting
About
Inference of Privacy-Preserving Portrait Matting (P3M)
This algorithm proposes inference with Privacy-Preserving Portrait Matting (P3M) model.
🚀 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 Workflowfrom ikomia.utils.displayIO import display# Init your workflowwf = Workflow()# Add the real_esrgan algorithmalgo = wf.add_task(name = 'infer_p3m_portrait_matting', auto_connect=True)# Run on your imagewf.run_on(url="https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_portrait.jpg")# Inspect your resultsdisplay(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.
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If you haven't started using Ikomia Studio yet, download and install it from this page.
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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 Workflowfrom ikomia.utils.displayIO import display# Init your workflowwf = Workflow()# Add the p3m process to the workflowalgo = wf.add_task(name="infer_p3m_portrait_matting", auto_connect=True)# Set process parametersalgo.set_parameters({"model_name" : "resnet34","input_size" : "1024","method": 'HYBRID',"cuda" : "True"})# Run workflow on the imagewf.run_on(url="https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_portrait.jpg")# Inspect your resultsdisplay(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 workflowwf = Workflow()# Add algorithmalgo = wf.add_task(name="infer_p3m_portrait_matting", auto_connect=True)# Run on your imagewf.run_on(url="https://raw.githubusercontent.com/Ikomia-dev/notebooks/main/examples/img/img_portrait.jpg")# Iterate over outputsfor output in algo.get_outputs():# Print informationprint(output)# Export it to JSONoutput.to_json()
Developer
Ikomia
License
MIT License
A short and simple permissive license with conditions only requiring preservation of copyright and license notices. Licensed works, modifications, and larger works may be distributed under different terms and without source code.
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