DLPy features include the following:
-
Read in and build deep learning models for image, text, audio and time series data.
- High-level APIs for:
- Deep neural networks for tabular data.
- Image classification and regression.
- Object detection.
- RNN-based tasks – text classification, text generation and sequence labeling.
- RNN-based time series processing and modeling.
- Processing audio files and training deep learning algorithms to create a language model for speech recognition applications.
- Predefined network architectures such as LeNet, VGG, ResNet, DenseNet, Darknet, Inception and YoloV2 and Tiny_Yolo. And many are provided with pre-trained weights!
- Enhanced data visualization such as heat maps and feature maps to aid in the interpretation of deep learning computer vision models.
- Import and export deep learning models in ONNX format.
DLPy can be used from Jupyter Notebook, JupyterLab, or from any Python console/scripting environment.
DLPy is open source and available on GitHub and PyPI. User contributions are accepted.
Get Started
Find all DLPy pre-requisites, installation, and configuration on sassoftware.github.io/python-dlpy/.
pip install sas-dlpy
conda install -c sas-institute sas-dlpy
You can also download from the GitHub repository and install locally.
Deep Learning with Python (DLPy) Computer Vision Demo Series
Introduction to the DLPy computer vision video series
Introduction to the DLPy computer vision video series
Leverage the Functional API with DLPy to build complex models for feature extraction, including a ResNet model
Image segmentation is achieved with a U-Net model to track soccer players
Image segmentation is achieved with a U-Net model to track soccer players
DLPY supports object detection with Faster R-CNN using VGG16 as the backbone network
DLPY supports object detection with Faster R-CNN using VGG16 as the backbone network
DLPy supports MobileNet and ShuffleNet and compares the performance of those models with a ResNet50 model
Multi-task learning is performed for training in the retail domain for product recommendations
Multi-task learning is performed for training in the retail domain for product recommendations
Multi-task learning is performed for inferencing in the retail domain for product recommendations
Multi-task learning is performed for inferencing in the retail domain for product recommendations
DLPy and SAS® Viya® Demo Resources
DLPy and SAS Viya - Introduction
Introduction
DLPy and SAS Viya - Image Classification with Convolutional Neural Networks
Image Classification with Convolutional Neural Networks
DLPy and SAS Viya - Obj Detection With Tiny YOLOv2 Model
Obj Detection With Tiny YOLOv2 Model
DLPy and SAS Viya - Import and Export Deep Learning Models With ONNX
Import and Export Deep Learning Models With ONNX
DLPy and SAS Viya - Text Class. and Text Generation With Recurrent Neural Networks
Text Class. and Text Generation With Recurrent Neural Networks
DLPy and SAS Viya - Time Series Forecasting With Recurrent Neural Networks
Time Series Forecasting With Recurrent Neural Networks
Samples
Example Notebooks and use cases can be found at sassoftware/python-dlpy/examples.
Sample Notebook Screenshots
Resources
DLPy Blogs & Communities
DLPY Blogs
SAS Support Communities
Data Mining and Machine Learning Community
DLPy Community Articles