What is MNN?
It is a lightweight deep neural network inference engine. It loads models and do inference on devices. At present, it has been integrated in more than 20 apps of Alibaba-inc, such as Taobao, Tmall, Youku and etc., covering live broadcast, short video capture, search recommendation, product searching by image, interactive marketing, equity distribution, security risk control and other scenarios. In addition, it is also used on embedded devices, such as IoT.
MNN is a tool in the Development & Training Tools category of a tech stack.
Key Features
Optimized for devices, no dependencies, can be easily deployed to mobile devices and a variety of embedded devicesSupports Tensorflow, Caffe, ONNX, and supports common neural networks such as CNN, RNN, GANHigh performanceEasy to use
MNN Pros & Cons
Pros of MNN
No pros listed yet.
Cons of MNN
No cons listed yet.
MNN Alternatives & Comparisons
What are some alternatives to MNN?
TensorFlow
TensorFlow is an open source software library for numerical computation using data flow graphs. Nodes in the graph represent mathematical operations, while the graph edges represent the multidimensional data arrays (tensors) communicated between them. The flexible architecture allows you to deploy computation to one or more CPUs or GPUs in a desktop, server, or mobile device with a single API.
PyTorch
PyTorch is not a Python binding into a monolothic C++ framework. It is built to be deeply integrated into Python. You can use it naturally like you would use numpy / scipy / scikit-learn etc.
scikit-learn
scikit-learn is a Python module for machine learning built on top of SciPy and distributed under the 3-Clause BSD license.
