chitra 0.0.12

Image utility library for Deep Learning

Chitra

Image utility library for Deep Learning

What is CHITRA

Chitra (चित्र) is an image utility library for Deep Learning tasks. (It is not image-processing library.)

Chitra reduces image data loading boilerplates for classification and object-detection.

It can also generate bounding-boxes from the annotated dataset.

If you have more use cases please raise an issue with the feature you want.

Installation

Using pip (recommended)

pip install -U chitra

Manually

git clone https://github.com/aniketmaurya/chitra.git

cd chitra

pip install -e .

How to use

Loading data for image classification

import numpy as np
import tensorflow as tf
import chitra
from chitra.dataloader import Clf, show_batch
import matplotlib.pyplot as plt

path = '/Users/aniket/Pictures/data/train'

clf_dl = Clf()
data = clf_dl.from_folder(path, target_shape=(224, 224))

clf_dl.show_batch(8, figsize=(8,8))

CLASSES ENCODED: {'cat': 0, 'dog': 1}

for e in data.take(1):
    image = e[0].numpy().astype('uint8')
    label = e[1].numpy()
plt.imshow(image)

<matplotlib.image.AxesImage at 0x7fee1000df10>

Visualization

Image annotation

Thanks to fizyr keras-retinanet

from chitra.visualization import draw_annotations

labels = np.array([label])
bbox = np.array([[30, 50, 170, 190]])
label_to_name = lambda x: 'Cat' if x==0 else 'Dog'

draw_annotations(image, ({'bboxes': bbox, 'labels':labels,}), label_to_name=label_to_name)
plt.imshow(image)

<matplotlib.image.AxesImage at 0x7fee0fe37890>