Run Neural Style Transfer algorithm.
We strongly recommend using a virtual environment. If you're not sure where to start, we offer a tutorial here.
pip install ikomia
[Change the sample image URL to fit algorithm purpose]
from ikomia.dataprocess.workflow import Workflow
from ikomia.utils.displayIO import display
# Init your workflow
wf = Workflow()
# Add algorithm
algo = wf.add_task(name="infer_neural_style_transfer", auto_connect=True)
# Run on your image
wf.run_on(url="https://cdn.pixabay.com/photo/2017/07/11/14/22/pont-du-gard-2493762_960_720.jpg")
# Display transferred style
display(algo.get_output(1))
# Display result
display(algo.get_output(0))
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.
- method (str, default="instance_norm"): method used to train the model. Must be "eccv16" or "instance_norm".
- model_name (str, default="candy"): pre-trained model name.
Model names available per method: - eccv16
- the_wave
- la_muse
- composition_vii
- starry_night
- instance_norm
- candy
- mosaic
- the_scream
- udnie
- feathers
- la_muse
- backend (str, default="Default"): backend.
- target (str, default="CPU"): target.
Note: parameter key and value should be in string format when added to the dictionary.
from ikomia.dataprocess.workflow import Workflow
from ikomia.utils.displayIO import display
# Init your workflow
wf = Workflow()
# Add algorithm
algo = wf.add_task(name="infer_neural_style_transfer", auto_connect=True)
algo.set_parameters({
"method": "eccv16",
"model_name": "la_muse"
})
# Run on your image
wf.run_on(url="https://cdn.pixabay.com/photo/2017/07/11/14/22/pont-du-gard-2493762_960_720.jpg")
# Display transferred style
display(algo.get_output(1))
# Display result
display(algo.get_output(0))
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_neural_style_transfer", auto_connect=True)
# Run on your image
wf.run_on(url="example_image.png")
# Iterate over outputs
for output in algo.get_outputs()
# Print information
print(output)
# Export it to JSON
output.to_json()