Automation of the creation of the architecture of the neural network based on the input
Project description
Auto-Deep-Learning (Auto Deep Learning)
auto_deep_learning
: with this package, you will be able to create, train and deploy neural networks automatically based on the input that you provide.
Installation
Use the package manager pip to install auto_deep_learning.
To install the package:
pip install auto_deep_learning
If using an old version of the package, update it:
pip install --upgrade auto_deep_learning
Basic Usage
Dataset
The data that it expects is a pd.DataFrame(), where the columns are the following:
- image_path: the path to the image
- class1: the classification of the class nr. 1. For example: {t-shirt, glasses, ...}
- class2: the classification of the class nr. 2. For example: {summer, winter, ...}
- ...
- split_type: whether it is for training/validation/testing
For better performance, it is suggested that the classes and the type are of dtype category in the pandas DataFrame. If the type is not provided in the dataframe, you should use the utils function of data_split_types (in utils.dataset.sampler file).
If instead you have the images ordered in the structure of ImageFolder, which is the following structure:
train/
class1_value/
1.jgp
2.jpg
...
class2_value/
3.jpg
4.jpg
...
test/
class1_value/
1.jgp
2.jpg
...
class2_value/
3.jpg
4.jpg
...
For simplifying logic, we have provided a logic that gives you the expected dataframe that we wanted, with the function of image_folder_convertion (in utils.functions), where it is expecting a path to the parent folder where the train/ and /test folders are.
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