error: when i execute 1st item in setup

[Ronald Omegna]

folks,

i installed python, tried the 1st test: 

C:\google-python-exercises> python hello.py Hello World

i am on win10; and i included 2 statements into the user environment path:

- one addition for where python is installed

- one addition for where the google-python-exercises  are installed

python was confirmed found from cmd line (using win10) 

but i got the following when i tried hello.py: i got syntax error 'missing parentheses in call to 'print'. did you mean print('Hello', name)?

i tried this from the cmd line and also when i tried it under IDLE

when i tried 'hello.py ron', it gave me a syntax error pointing to 'ron'; name 'hello' is not defined

ok, i know i am doing something wrong, but i can't figure out what.

any help is appreciated. has to be something simple?

thanks,

ron

[Prabhat upadhyay]

SURE

[Darshan Bafna]

You should directly install it from Microsoft Store i.e pychram

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[Sudhagar V]

If your running your program in cmd. First you have to local your path on your cmd. And type

Python hello.py

This cmd used for running your python program.

Again if you getting an error. Just go to your environmental variable tool window and check whether python path has correctly inserted or not. 

After everything over. Just check your python version using your cmd.

To view this discussion on the web visit https://groups.google.com/d/msgid/python-gcu-forum/CACN%2BTx%2BujVCQW0nu8MOBZ5aM%3DJpMghLeuRqSvZqo_S2PfRrJhA%40mail.gmail.com.

[e learn]

check version, both python 2.x and 3.x uses print differently

Small advice, post your code or code link. 

use online tool as well like google colab, replit.com

regards

Pavneet

[Vimalkumar Chawda]

Hello Everyone Sir

I have good knowledge of matlab but new to python. Can you please help me to read few lines of matlab to python? My code is below and I mention too detailed all the data. I am ready to pay for if someone can help me within short notice also. Thank you all.  

close all

clear all

clc

%% Read image sequence

path2sequence = 'sequence';

search_string = fullfile(path2sequence, '*.jpeg');

file_list = dir(search_string);

%% Sequencial estimation of the gaussians parameters

% TODO: Learning rate

alpha = 1/50;

% Initial values

im_RGB = imread(fullfile(path2sequence, file_list(1).name));

[m,n] = size(rgb2gray(im_RGB));

 

mu = single(rgb2gray(im_RGB)); 

sigma_square = ones(m,n)*100;

% Structure element for morphological operation

se = strel('square',3);

h1 = figure(1);

colormap(gray);

dim = [0 0 1 1];%[0.262499999999998,0.002380951174668,0.480357129073569,0.06428571307943];

txt = [sprintf('Learning Rate: % .2f,  Number of Frames: % .2f' ,alpha,inv(alpha))];

ui = annotation('textbox',dim,'String',txt,'FitBoxToText','on','verticalalignment', 'bottom');

% Iterate over the sequence

for i = 2:length(file_list)

    im_RGB = imread(fullfile(path2sequence, file_list(i).name));

    im = single(rgb2gray(im_RGB));

    

    % TODO: Thresholding for background subtraction

    %variance is used as a local threshold

    delta_g = abs(im-mu);

    %background and foreground pixels are initialized with as 1

    mask_back = ones(m,n); %-> background pixels are 1, foreground pixels are set to 0

    mask_back(delta_g > 2.5*sqrt(sigma_square)) = 0; % setting foreground to 1 using the threshold

    mask_back = logical(mask_back); %convert to type "logical"

    

    % Eliminate noise

    % TODO: Closing using structure element "se"

    filtered_mask = imclose(mask_back,se);

    

    % Update Gaussian parameters 

    % TODO: Mean

    mu = (alpha * im) + ((1-alpha)*mu); %updating the mean

    % TODO: Variance

    sigma_square = (alpha * (mu - im).^2) + (1-alpha) * sigma_square; %updating the variance

    

    % Output

    subplot(231); 

    imagesc(im, [0 255]); % TODO: Show input image

    title('Input Image')

    subplot(232); 

    imagesc(mu, [0 255]); % TODO: Show mean values

    title('Mean Image')

    subplot(233);  

    imagesc(sigma_square, [0 255]); % TODO: Show variances

    title('Variance Image')

    subplot(234);  

    imagesc(delta_g, [0 255]); % TODO: Show difference between current image and mean values

    title('Delta_G Image')

    subplot(235);  

    imagesc(mask_back, [0 1]); % TODO: Show background mask (unfiltered)

    title('Unfiltered Image')

    subplot(236);  

    imagesc(filtered_mask, [0 1]); % TODO: Show background mask after eliminating noise

    title('Filtered Image')

    drawnow; 

%     txt = [sprintf('Frame No.: % .2f' ,i)];

    txt = [strcat("Frame Number",int2str(i))];

    box = annotation('textbox',dim,'String',txt,'FitBoxToText','on');

    pause(0.00000000001);

    delete(box)

end

[Vimalkumar Chawda]

My first task is read all the images as which is available in set of images. 

How we can read the video which is set of images? I want to apply Gaussian on it. Thanks  

[Vimalkumar Chawda]

this is the first image of the sequence and last image is below