alievk/ai_utilities

ai_utilities

A set of scripts useful in deep learning and AI purposes, originally for use with fast.ai lectures and libraries.

image_download.py

Download images (typically limited to 1000) from a specified serach engine, currently Google or Bing. image_download.py is useful in several respects:

• Because is utilizes selenium, it is not limited by the search engine api and generally allows for more downloaded images.
• It can operate in headless mode, which means it can be used on a server without access to a gui browser.
• The default browser is Firefox. The script can be modified to use other browsers such as Chrome.

usage: image_download.py [-h] [--gui] [--engine {google,bing}]
                         searchtext num_images

Select, search, download and save a specified number images using a choice of
search engines

positional arguments:
  searchtext            Search Image
  num_images            Number of Images

optional arguments:
  -h, --help            show this help message and exit
  --gui, -g             Use Browser in the GUI
  --engine {google,bing}, -e {google,bing}
                        Search Engine, default=google

Example: image_download.py 'dog' 200 --engine 'bing' --gui

Installation:

• virtualenv -p python3.6 env
• source env/bin/activate
• pip install -r requirements.txt
• Install an appropriate browser and browser driver (appropriate for your browser and operating system) in PATH. For example, if using Ubuntu and Firefox:
• tar xfvz geckodriver-v0.19.1-linux64.tar.gz
• mv geckodriver ~/bin/, where ~/bin is a dir in PATH

make_train_valid.py

usage: make_train_valid.py [-h] [--train TRAIN] [--valid VALID] [--test TEST]
                           labels_dir

Make a train-valid directory and randomly copy files from labels_dir to sub-
directories

positional arguments:
  labels_dir     Contains at least two directories of labels, each containing
                 files of that label

optional arguments:
  -h, --help     show this help message and exit
  --train TRAIN  files for training, default=.8
  --valid VALID  files for validation, default=.2
  --test TEST    files for training, default=.0

For example, given a directory:

catsdogs/
         ..cat/[*.jpg]
         ..dog/[*.jpg]

make_train_valid.py catsdogs --train .75 --valid .25

Creates the following directory structure:

catsdogs/
         ..cat/[*.jpg]
         ..dog/[*.jpg]
         ..train/
                 ..cat/[*.jpg]
                 ..dog/[*.jpg]
         ..valid/
                 ..cat/[*.jpg]
                 ..dog/[*.jpg]

filter_img.sh

Use file to determine the type of picture then filter (keep) only pictures of a specified type.

Images are filtered in place, i.e., non-JPEG files are deleted. (This can be modified within the script.)

Usage: filter_img image_directory

Example:filter_image dogs/

Sample workflow

image_download.py 'bmw' 500 --engine 'bing' --gui
image_download.py 'cadillac' 500 --engine 'google'
mv dataset cars
filter_img.py cars/bmw
filter_img.py cars/cadillac
make_train_valid.py cars --train .75 --valid .25