Facial feature segmentation neural network

Product Description

Facial feature segmentation deep neural network segments a face image into several distinguished semantic areas. The general facial segmentation deep neural network handles ten different facial semantic feature areas:

• Eyes (Left and right separate) NEW
• Nose
• Mouth
• Ears (Left and right separate) NEW
• Teeth
• Hair
• Eyebrows (Left and right separate) NEW
• Facial hear / beards
• Specs / Sunglasses
• General Face

Faceprocessor V2 has been trained  using a large range of facial poses from different camera facing angles. Ranging  from frontal portraits to side facing face images reaching up to 110 degrees

You have total freedom in how you want to deploy the model. You can put it on a server, public or private cloud. Or alternatively use it directly in your application or on an edge device. This choice is totally up to you. There are no constraints and you do not pay any transaction fees for using the model from Mut1ny

The model is deliverable in these supported neural network formats*

*In your order please use the additional field to indicate which neural network format you would prefer

What is included in the facial feature segmentation deep neural network?

• The model in the network framework format of your choice (see above)
• For ONNX format only:
  • an inference script in Python using ONNXRuntime our recommended ONNX inference framework
  • C# code for using our Model using  ONNXRuntime
  • C++ code for using our Model using ONNXRuntime
  • A deployment script for using our Model in combination with AzureMachineLearning
• For PyTorch only:
  • an inference script in Python using PyTorch
  • C++ code for using our Model using PyTorch
• For mxnet only
  • An inference script in Python using mxnet and gluoncv

Why buy a deep neural network model? When you can build and train one yourself? Or get one free from the internet? 

• Training a segmentation model from scratch using a  large enough dataset takes between 2-3 days even with a high-end equipped GPU. This translates to € 80-150,- public cloud instance spending costs alone.
• There is no need to spend any development time, but instead you can fully concentrate on your product feature.
• Acquiring a large enough annotated dataset can take man-months.
• To our knowledge there are no public facial segmentation models available that cover a similar range in gender,ethnicity,age & pose. Those that do exist most likely have a very restrictive licensing scheme.

Why go for a subscription instead of single one-off purchase?

• Subscription allows you take advantage of Mut1ny’s future neural network model improvements. We improve our neural network models on a permanent basis adopting to latest research developments. This mean you benefit from our research and therefore will get better models over time.
• Subscription allows you take advantage of Mut1ny’s constantly growing training set. We constantly enlarge our training set with new data to cover a wider variety. If you are  subscription user and you do encounter cases that do not produce a satisfactory result  you can send it to us. We’ll be happy to include it in our training set.