Facial Expression Recognition with PyTorch

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在此免费指导项目中,您将:
2 hours
面向初学者
无需下载
分屏视频
英语(English)
仅限桌面

In this 2-hour long guided-project course, you will load a pretrained state of the art model CNN and you will train in PyTorch to classify facial expressions. The data that you will use, consists of 48 x 48 pixel grayscale images of faces and there are seven targets (angry, disgust, fear, happy, sad, surprise, neutral). Furthermore, you will apply augmentation for classification task to augment images. Moreover, you are going to create train and evaluator function which will be helpful to write training loop. Lastly, you will use best trained model to classify expression given any input image.

必备条件

您要培养的技能

  • Deep Learning

  • Convolutional Neural Network

  • pytorch

  • classification

  • Computer Vision

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在与您的工作区一起在分屏中播放的视频中,您的授课教师将指导您完成每个步骤:

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