labelvis 0.0.1

python library to visualize object detection labels

labelvis

This is a small python utility to quickly visualize bounding-box annotations/labels before training models on the data.

Installation

git clone https://github.com/satheeshkatipomu/labelvis.git
cd labelvis
pip install -e .

Usage

COCO

from labelvis.labelvis import LabelVisualizer

imgs_path = "./images"
annotations_path = "./annotations/trainval.json"
annotations_format = "coco" #["coco","pascal","manifest","yolo"]
img_size = 256
labelvis = LabelVisualizer(imgs_path,annotations_path,annotations_format,img_size=img_size)

num_images = 9 #Number Images to Visualize
labelvis.show_batch(num_imgs=num_images)

Output

Input format

Images

Common for all annotations formats.

imgs_path = "/path/to/images"

    /path/to/images
         |_ img001.jpg
         |_ img002.jpg
         |_ img003.jpg
     ...

Annotations

COCO (x,y,w,h)

annotations_path = "/path/to/annotations/annotations.json"

Pascal

annotations_path = "/path/to/annotations"
    /path/to/annotations
         |_ img001.xml
         |_ img002.xml
         |_ img003.xml
         ...

Manifest (output from AWS Sagemaker groundtruth)

annotations_path = "/path/to/annotations/output.manifest"

Yolo

annotations_path = "/path/to/annotations"
    /path/to/annotations
         |_ img001.txt
         |_ img002.txt
         |_ img003.txt
         ...