dataset_via

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.

🚀 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

[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()

☀️ 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

• 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"
})