NVIDIA DIGITS

What is NVIDIA DIGITS?

NVIDIA DIGITS is the first interactive Deep Learning GPU Training System. DIGITS is a new system for developing, training and visualizing deep neural networks. It puts the power of deep learning into an intuitive browser-based interface, so that data scientists and researchers can quickly design the best DNN for their data using real-time network behavior visualization. DIGITS is open-source software, available on GitHub, so developers can extend or customize it or contribute to the project.

  • Design, train and visualize deep neural networks for image classification, segmentation and object detection
  • Download pre-trained models from the DIGITS Model Store
  • Perform hyperparameter sweep of learning rate and batch size for improved model accuracy
  • Schedule, monitor, and manage neural network training jobs, and analyze accuracy and loss in real time
  • Import a wide variety of image formats and sources
  • Scale training jobs across multiple GPUs automatically

NVIDIA DIGITS
CONSOLE EXAMPLE

Why NVIDIA DIGITS?

  • User-friendly interface for training and classification that can be used to train DNNs with a few clicks.
  • The DIGITS interface provides tools for DNN optimization. The main console lists existing databases and previously trained network models available on the machine, as well as the training activities in progress.
  • DIGITS makes it easy to visualize networks and quickly compare their accuracies.
  • Easy for a team of users to share datasets and network configurations, and to test and share results.
  • DIGITS integrates the popular Caffe deep learning framework , and supports GPU acceleration using cuDNN to massively reduce training time.

Who is NVIDIA DIGITS for?

Data Scientists & Researchers That Need To:

  • Quickly design the best deep neural network (DNN) for the data
  • Monitor DNN training quality in real-time
  • Manage training of many DNNs in parallel on multi-GPU systems, and multi-GPU training

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NVIDIA DIGITS Examples and Applications

Object Detection with DIGITS:
DIGITS 4 includes DetectNet, a new network architecture that simultaneously performs object classification and a regression to estimate object bounding boxes.


Image Segmentation Using DIGITS 5:
Semantic segmentation attempts to partition an image into regions of pixels that can be given a common label.