dcholee/video_place_recognition

VTT 3rd year

video_place_recognition

VTT 3rd year

Place recognition software for Friends video based on scene change detector

This repository contains codes and pre-trained checkpoints of a place recognition model and scene change detector for Friend video.

Requirements

• Ubuntu(Tested on v16.04)
• Python 2.7
• Pytorch(Tested on v1.2.0)
• NumPy
• PIL
• opencv-python
• matplotlib
• jsonl

Download pre-trained checkpoint

Pre-trained checkpoint should be placed in the root directory. You can download the checkpoint at here : https://drive.google.com/open?id=1kmbdXIj9YkH_XYehaozdhwsRcAyCpadN

How to use

Input : video file (e.g. *.avi, *.mkv) Output : jsonl file (predicted class of video frames for every second, 1fps)

Below is an example of output jsonl file.

{"second": 0.0, "type": "location", "class": "none"}
{"second": 0.0, "type": "location", "class": "none"}
...
{"second": 52.0, "type": "location", "class": "cafe"}
{"second": 53.0, "type": "location", "class": "cafe"}
...
{"second": 314.0, "type": "location", "class": "home-livingroom-Monica"}
{"second": 315.0, "type": "location", "class": "home-livingroom-Monica"}

You can run following command on a terminal,

python demo.py --input_filename <video-file> --output_filename <output-file-name>

For example

python demo.py --input_filename input.mkv --output_filename output

Then output.jsonl file will be saved in the root directory

Acknowledgements

This project was supported by Institute for Information & communications Technology Promotion(IITP) grant funded by the Korea government(MSIT) (2017-0-01780, The technology development for event recognition/relational reasoning and learning knowledge based system for video understanding)