Genetic algorithm for calculate linear intersection

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I want to build a genetic algorithm to calculate efficiently linear intersections.
Maybe some different impleentations could be tested to select the most suitable one
What i want is a modified Bentley Ottman algorithm (or similar) and another linear intersection algortihm of your choise (e.g. regular sweep line algorithm). They will be modified through genetic algorithm and implemented in Python. Their complexity (eg O(logN) will be tested and we will fine tune them slightly to see if the performance can be improved. A description of how they work and what they do with some figures will be also provided and also the performance results. These will be tested on synthetic results (random linear objects), but i will also have the ability to load my own data (shapefile) to run the algorithm
i have an already developed unity project with few errors. I have a python deep learning model which predicts the coordinates of human skeleton in a 3d plane. The input to this deep learning model is the coordinates of joints of the skeleton and trajectory which can be draw once at each joint. We have a 17 joint skeleton system from h3.6m dataset. I've created a web unity app and established a connection between this model and unity app. In the app, user can input three initial poses and user can draw trajectory at each joint. After this user press a button and all this data will go the deep learning model and predictions are being made. These predictions are sent back to unity interface and we create an animation using these predictions. I have few errors in this project (mostly at unity interface). I need it very urgently. Thanks.

then run exe file:

https://drive.google.com/file/d/1YFqusmC8_zwK4tC2OjQalbQf1oO1jFoi/view?usp=sharing

ok so, you have to install torch version 1.7

then run server.py from trajevae/code folder

let me know when you are done

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