Load VGG Image Annotator (VIA) dataset. This plugin converts a given dataset in VIA format to Ikomia format. Then, any training algorithms from the Ikomia marketplace can be connected to this converter.
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 import ik
# Initialize the workflow
wf = Workflow()
# Add the dataset loader to load your custom data and annotations
dataset = wf.add_task(name="dataset_via")
# Set parameters
dataset.set_parameters({
"via_json_file":"Path/to/via_json_file.json"
})
# Add the YoloV8 training algorithm
yolo = wf.add_task(name="train_yolo_v8")
# Launch your training on your data
wf.run()
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.
- via_json_via (str): Annotation file (.json).
from ikomia.dataprocess.workflow import Workflow
from ikomia.utils import ik
# Initialize the workflow
wf = Workflow()
# Add the dataset loader to load your custom data and annotations
dataset = wf.add_task(name="dataset_via")
# Set parameters
dataset.set_parameters({
"via_json_file":"Path/to/via_json_file.json"
})