Deep Learning Platform (DLP) is a piece of software for AI application development and composed of main modules of a DL application pipeline: Data, Net, Train, Deploy.
DLP aims to release developers from coding but focus on designing networks.
Play with it and enjoy.
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Support Keras
New Deploy Module
User Guide 3.0 (CN)
Support Tensor Core
Network Library
User Guide 2.5 (CN)
Docker-based
Object Detection
User Guide(CN)
DLP data module provides multiple data processing functions: image classification, object detection, image segmentation and etc.
With mouse clicking and dragging, developers can easily do labeling for various tasks.
DLP can even combine labelings from multiple users.
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DLP net module provides a playground for developers to try different network structures.
With simple dragging and connecting, a network can be easily constructed.
Unleash your genius, and create novel networks.
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Training visualization module allows developers to monitor the training progress with nice graphs and log panels.
Developers can do parameter studies in DLP efficiently with peer-to-peer comparisons.
Graphs are always the best media to interpret numbers.
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It should be exciting to try your model after numerous epochs of training.
DLP provides a nice module for you to see how your model works with a simple configuration.
With a simple click, your model can be launched.
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