Utility functions for the fast ai mooc
Project description
# duckgoose
Utils for the online [fast.ai](www.fast.ai) course
## Installation
## Prerequisites
## `fetchImagesAndPrepForClassification`
Utility for Lesson 1 experimentation with external classes. The script:
* Downloads images from google images download for specific classes
* Sanity check that images can be opened and have three channels
* Organises the images into separate folders (train/valid/test + classes) as expected by the fast.ai library
### Quick example
```python
from duckgoose.image_classification_bootstrap import fetchImagesAndPrepForClassification
# dictionary structure `class_name => search term`
image_classes = { 'ducks' : 'ducks -rubber' , 'geese' : 'geese' }
download_path = '/home/myuser/data/downloaded_from_google'
output_path = '/home/myuser/data/ducksgeese/'
number_of_images = 100
fetchImagesAndPrepForClassification(image_classes, download_path, output_path, number_of_images)
```
# License
[The MIT License (MIT)](LICENSE.txt)
Utils for the online [fast.ai](www.fast.ai) course
## Installation
## Prerequisites
## `fetchImagesAndPrepForClassification`
Utility for Lesson 1 experimentation with external classes. The script:
* Downloads images from google images download for specific classes
* Sanity check that images can be opened and have three channels
* Organises the images into separate folders (train/valid/test + classes) as expected by the fast.ai library
### Quick example
```python
from duckgoose.image_classification_bootstrap import fetchImagesAndPrepForClassification
# dictionary structure `class_name => search term`
image_classes = { 'ducks' : 'ducks -rubber' , 'geese' : 'geese' }
download_path = '/home/myuser/data/downloaded_from_google'
output_path = '/home/myuser/data/ducksgeese/'
number_of_images = 100
fetchImagesAndPrepForClassification(image_classes, download_path, output_path, number_of_images)
```
# License
[The MIT License (MIT)](LICENSE.txt)
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