pip install ikomia
About
1.1.1
Apache-2.0
Inference of MODNet Portrait Matting.
This algorithm proposes inference with MODNet a trimap-free portrait matting in real time.
🚀 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.
2. Create your workflow
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_modnet_portrait_matting", auto_connect=True)
# Run workflow on the image
wf.run_on(url="https://images.pexels.com/photos/12508998/pexels-photo-12508998.jpeg")
# Inspect your results
display(algo.get_input(0).get_image())
display(algo.get_output(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
- input_size (int) - default: '800': Size of the input image (stride of 32)
- 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_modnet_portrait_matting", auto_connect=True)
# Set process parameters
algo.set_parameters({
"input_size" : "800",
"cuda" : "True"})
# Run workflow on the image
wf.run_on(url="https://images.pexels.com/photos/12508998/pexels-photo-12508998.jpeg")
# Inspect your results
display(algo.get_input(0).get_image())
display(algo.get_output(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.
import ikomia
from ikomia.dataprocess.workflow import Workflow
# Init your workflow
wf = Workflow()
# Add algorithm
algo = wf.add_task(name="infer_modnet_portrait_matting", auto_connect=True)
# Run on your image
wf.run_on(url="https://images.pexels.com/photos/12508998/pexels-photo-12508998.jpeg")
# Iterate over outputs
for output in algo.get_outputs():
# Print information
print(output)
# Export it to JSON
output.to_json()
Developer
Ikomia
License
Apache License 2.0
A permissive license whose main conditions require preservation of copyright and license notices. Contributors provide an express grant of patent rights. Licensed works, modifications, and larger works may be distributed under different terms and without source code.
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|---|---|---|
Commercial use | License and copyright notice | Trademark use |
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This is not legal advice: this description is for informational purposes only and does not constitute the license itself. Provided by choosealicense.com.