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NYCU-VST-2023-fall

HWs of Video Streaming and Tracking 2023 Fall NYCU

HW1

In this assignment, you will practice constructing a neural network using PyTorch and training it to perform a classification task.
To ensure that students can meet the assignment's requirements, the use of pretrained weights and existing models, such as those built with torchvision, is not permitted.

HW2

• Train a neural network to do detection on our own dataset
• Model: object detection algorithms
• YOLOX (we use the official code to set the baseline)
• Add SE module to your network
• Framework: PyTorch

HW3

• Implement visual multiple object tracking on videos.
• Using detection model + Hungarian algorithm.
• Calculate the total number of people appearing in the video.
• Output the tracking result video and the count result.

HW4

You are asked to build a Live Streaming Server and perform tasks using deep learning model.

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