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tyiannak / multimodal_movie_analysis

A Python Library for Multimodal Analysis of Movies and Content-based Movie Recommendation
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Shot Evaluation: experiments for different shot_change() parameters #14

Open tyiannak opened 3 years ago

tyiannak commented 3 years ago

@apoman38 @electrasif can you split the experiments and select the optimal set of parameters? Use master branch and the shot_evaluation script for different thresholds in the shot_change. In particular, create a set of values for the thresholds in line 411 and report the precision and recall in a spreadsheet. Lets try 30 or 40 combinations of threshold values and select the best. You can split experiments in half. Can you have this until tuesday @electrasif @apoman38 ?

apoman38 commented 3 years ago

Yes, of course! I will discuss with @electrasif for the experiments.

apoman38 commented 3 years ago

Can I make the experiments with the old version of analyze_visual.py? The new version with object detection wich using PyTorch is very very slow and there are many experiments.

tyiannak commented 3 years ago

no i would prefer to use the current version. if it is too slow u can temporarily cache the features (and not commit the code) for each video file

apoman38 commented 3 years ago

The first phase of the experiments was completed. Our goal was to find out how each variable affects precision and recall. The method we followed to achieve this was to keep two of the three variables constant and change values ​​in the remaining variable. Below we suggest which range of variables we consider appropriate to perform grid search.

if ((mag_mu> [0.04,0.05,0.06,0.08,0.1]) and (gray_diff > [0.002,0.02,0.04,0.05,0.06]) and (f_diff[-1] >[0.22,0.55,0.75,0.95,1,5]))

Are the above values ​​right to proceed with the grid search process? Below is the spreadsheet with the experiments. (https://docs.google.com/spreadsheets/d/1JgvNMInXPCZjImzHFCqa1mJlwntHmxZ2DjScwJtimQ8/edit?usp=sharing)