puck | fast parser for natural languages using GPUs | Parser library

Context:

We are building a robot that will be assigned a color of puck to pick up and will need to go grab it. So for that, from the world view camera, he will get the approximate coordinates.

I first used HoughCircles to find the centers of each circles, but then i realized that i would also need to know the colors of corresponding circles found, so i tried an other approach ( see below).

Note: circles will be placed randomly, no no hardcoding.

Here's whats the image looks like :

Problem:

Very hard to get accurate HSV value to correctly detect the colors in the title, plus the image quality is not the best. I think the middle circle in those pucks is to help us distinguish them but as most have a light blue circle in it, im not sure how it helps haha.

What i tried:

1.

I used openCV trackbar, to get the approximate lower and upper bound for each color ( except those mentioned) which are really hard to get).

2.

I apply the mask on the picture and then find the center of circles with moments.

I am making a Swift game similar to Air Hockey in SpriteKit.

I am trying to have accurate/expected 'impulses' applied to the puck when it is struck by the player's mallet.

I have access to the player's velocity. I also have accurate collision detection between the two circles by using func didBegin(_ contact: SKPhysicsContact). Additionally I have the expected direction the ball should bounce based on where it struck the player's mallet (since its a circle this direction might be different than you would expect by looking at the player's dx and dy.)

This is what Im currently doing but it feels a bit unnatural and off:

I am trying to clean up data frame using dplyr , For each element in a specific column, keep only one element of the other columns and eliminating all the duplicates

In this case, for each part number ( Part_No) , I want to retain all unique values fpr all Operation (Op) , but eliminating duplicates.

I am trying to find a way to subset or filter my dataset (repeated measures of individuals) using a conditional statement on the first measure. In other words, I want to filter the dataset to only include data for all time points for the individuals which have a specific condition present at time point 1.

Example Data:

I have raised the SO Question here and blessed to have an answer from @Scott Boston.

However i am raising another question about an error ValueError: Columns must be same length as key as i am reading a text file and all the rows/columns are not of same length, i tried googling but did not get an answer as i don't want them to be skipped.

I am reading a file called kids_csv with header=None option, this file contains every row with specific alphabets along with : like ab:, ad: etc, I want the entire row to become a column where like ab: that's starting off the line needs to be designated as a column name.

below is my dataframe:

I'm trying to make a little game where the user can click on a place on the page, the circle will follow to the pointer's position, and from there, the user can drag their mouse to make the circle move like a slingshot. I want the circle to be able to bounce off the walls.

However, it seems that on the circle's collision with a wall, the circle seems to 'stick' to the wall instead of bouncing right off. I think it might be because of the circle changing directions too quickly due to a rounding error? Also the top wall's collision hasn't been implemented yet because I don't think I declared the top wall div object properly.

When I touch the player mallet (Air Hockey), I want to make it so the mallet moves slightly above the touch. This way the mallet will be more visible in the game. I have found some solutions but am having a hard time implementing properly in my function.

Here is a sample of my touchesMoved() function: