dataset_pascal_voc

Load PascalVOC dataset. This algorithm converts a given dataset in PascalVOC 2012 format to Ikomia format.

🚀 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

import ikomia
from ikomia.dataprocess.workflow import Workflow

# Init your workflow
wf = Workflow()

# Add algorithm
algo = wf.add_task(name="dataset_pascal_voc")

algo.set_parameters({
    "annotation_folder": "path/to/annotation/folder",
    "dataset_folder": "path/to/image/folder",
    "class_file": "path/to/classes/file.txt",
})

train = wf.add_task(name="train_yolo_v8", auto_connect=True)

# Run on your image  
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

annotation_folder (str): Path to the folder containing the annotation .xml files.
dataset_folder (str): Path to the image folder.
instance_seg_folder (str, optional): Path to segmentation masks folder‍.
class_file (str) = Path to text file (.txt) containing class names.