Build a Video to Slides Converter Application using the Power of Background Estimation and Frame Differencing in OpenCV

This repository contains code for Build a Video to Slides Converter Application using the Power of Background Estimation and Frame Differencing in OpenCV blogpost

Video to Slides Conversion using Frame Differencing and Background Estimation

Install required packages

After unzipping the file Build-a-Video-to-Slides-Converter-Application-using-the-Power-of-Background-Estimation-and-Frame-Differencing-in-OpenCV, run the following command in your virtual environment:

pip install -r requirements.txt

Execution

The command line flags are as follows:

• video_file_path: The path to the input video file.
• out_dir: The path to the output directory where the results would be stored.
• type: The type of background subtraction method to be applied. It can be one of: Frame_Diff, GMG (default), or KNN.
• no_post_process: flag to specify whether to apply the post-processing step. If not specified, the post-processing step is always applied as default.
• convert_to_pdf: flag to specify whether to convert the image set into a single PDF file.

An example usage can be:

python video_2_slides.py -v ./sample_vids/Neural_Networks_Overview.mp4 -o output_results --type GMG --convert_to_pdf

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