Lightweight package meant to simplify data processing for Deep Learning
Project description
Melon
Installation
Install and update using pip:
$ pip install melon
Supported in Python >= 3.4.0
Examples
Images
With default options:
from melon import ImageReader
def train():
source_dir = "resources/images"
reader = ImageReader(source_dir)
X, Y = reader.read()
...
with tf.Session() as s:
s.run(..., feed_dict = {X_placeholder: X, Y_placeholder: Y})
Since number of images may be too large to fit into memory the tool supports batch-processing.
from melon import ImageReader
def train():
source_dir = "resources/images"
options = { "batch_size": 32 }
reader = ImageReader(source_dir, options)
while reader.has_next():
X, Y = reader.read()
...
With custom options:
from melon import ImageReader
def train():
source_dir = "resources/images"
options = { "data_format": "channels_last", "normalize": False }
reader = ImageReader(source_dir, options)
...
Options
Images
- width
Width of the output (pixels). default: 255
- height
Height of the output (pixels). default: 255
- batch_size
Batch size of each read. default: All images in a directory
- data_format
Format of the images data
channels_first - Channel x Height x Width (default)channels_last - Height x Width x Channel- label_format
Format of the labels data
one_hot - as a matrix, with one-hot vector per image (default)label - as a vector, with a single label per image- normalize
Normalize data. default: True
- num_threads - number of threads for parallel processing
default: Number of cores of the machine
Labeling
Generating labels file
$ melon generate
> Source dir:
#legend
pedestrian:0
cat:1
parrot:2
car:3
apple tree:4
#map
img275.jpg:1
img324.jpg:2
img551.jpg:3
img928.jpg:1
img999.png:0
img736.png:4
Format of the labels
Label’s output format can be specified in Custom options. It defaults to one-hot format.
Roadmap
Support for textual data (Q1 2019)
Support for video data (Q1 2019)
Support for reading from AWS S3 (Q2 2019)
Project details
Release history Release notifications | RSS feed
Download files
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.