chitra 0.0.11

Library for creating data input pipeline in pure Tensorflow 2.x

Chitra

Library for creating data input pipeline in Tensorflow

Install

pip install chitra

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>

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>