"""
.. module:: view_train_images
:synopsis: Example nuts-ml pipeline reading and viewing image data
"""
from nutsflow import Take, Consume, MapCol
from nutsml import ViewImageAnnotation, PrintColType
if __name__ == "__main__":
from cnn_train import load_samples, load_names
train_samples, _ = load_samples()
names = load_names()
id2name = MapCol(1, lambda i: names[i])
show_image = ViewImageAnnotation(0, 1, pause=1, figsize=(2, 2),
interpolation='spline36')
(train_samples >> Take(10) >> id2name >> PrintColType() >>
show_image >> Consume())
:synopsis: Example pipeline for viewing annotations and classification
"""
from __future__ import print_function
from glob import glob
from nutsflow import Collect, Consume, Get, Zip, Map, ArgMax, Print
from nutsml import (TransformImage, BuildBatch, ReadImage, ViewImageAnnotation,
ConvertLabel)
BATCH_SIZE = 128
if __name__ == "__main__":
from cnn_train import create_network, load_names
convert_label = ConvertLabel(None, load_names())
rerange = TransformImage(0).by('rerange', 0, 255, 0, 1, 'float32')
show_image = ViewImageAnnotation(0, 1, pause=1, figsize=(3, 3),
interpolation='spline36')
pred_batch = BuildBatch(BATCH_SIZE).input(0, 'image', 'float32')
print('loading network...')
network = create_network()
network.load_weights()
print('predicting...')
samples = glob('images/*.png') >> Print() >> ReadImage(None) >> Collect()
predictions = (samples >> rerange >> pred_batch >>
network.predict() >> convert_label)
samples >> Get(0) >> Zip(predictions) >> show_image >> Consume()
"""
.. module:: write_images
:synopsis: Example nuts-ml pipeline for writing of images
"""
from nutsflow import (Take, Print, Consume, Enumerate, Zip, Format, MapCol,
Get)
from nutsml import WriteImage, ConvertLabel
if __name__ == "__main__":
from cnn_train import load_samples, load_names
train_samples, _ = load_samples()
convert_label = ConvertLabel(1, load_names())
fnames = (Enumerate() >> Zip(train_samples >> Get(1)) >> convert_label >>
Format('{0}_{1}') >> Print())
imagepath = 'images/img*.png'
train_samples >> Take(10) >> WriteImage(0, imagepath, fnames) >> Consume()