Python Automation and Machine Learning for EM and ICs

cv2.waitKey(1): Will display a frame for 1 ms, after which display will be automatically closed. Since the OS has a minimum time between switching threads, the function will not wait exactly 1 ms, it will wait at least 1 ms, depending on what else is running on your computer at that time.

close(): It closes the file or webpage, and frees the memory space acquired by that file.

win32clipboard.CloseClipboard()

Open and close any type of files with default programs/apps (e.g. word, excel, dm3, dm4, Digital Micrograph, powerpoint, internet explorer, chrome, and so on) in windows

Minimize/maximize/restore/activate/resize/move/close Window objects

Open and close specific files

Fill in closed curves

Methods to open google chrome (problems: Google chrome closes immediately after being launched with selenium) (with close-browser and quit-driver function)

Convolution and convolutional layers

Comparison of regression classes

Independent Component Analysis (ICA)

Convex optimization, convexity of loss functions, convex functions and convex sets

Cocktail party problem

Lipschitzness/Lipschitz continuity

Point-Biserial Correlation

Kendall Tau Rank Correlation Coefficient

Pearson Correlation Coefficient/Pearson's r/Correlation Coefficient

Spearman Rank Correlation/Spearman's rho/Spearman correlation

Epsilon cover/ε-cover/epsilon-net

Infinite Hypothesis Class

Finite Hypothesis Class/finite Hypothesis Analysis

Complementary inequality

Core Steps/Procedure/Designing of Machine Learning

Finite Hypothesis Class versus Infinite Hypothesis Class

Various names or terms that describe similar concepts or techniques in ML

Hypothesis class/hypothesis family/predictor class/model class/hypothesis family/predictor family/model family (h)

Concentration inequality

Central Limit Theorem (CLT)

Covariance matrix

Modify/replace the line in a text file if a line contains specific string

Well-specified case

Uniform convergence

Consistency in Statistics

Defect Detection and Classification by using Machine Learning

Cross entropy (log loss/logistic loss)

Trick: generic code/script templates for complex automation

Loss (risk, cost, objective) function

Confusion matrix heatmap

Common Words for Classification of Groups of Texts

Good research topics in the field of semiconductor manufacturing and computer vision

Autonomous vehicles/cars and machine learning

Classification tree/decision tree for classification

Fréchet Inception Distance (FID) coefficient

Misclassification rate (classification error rate or error rate) in machine learning

Corpus

Class Activation Mapping (CAM)

Comparison between supervised and unsupervised learning

Convert a list to a matrix

Execute a command on Command Prompt of Windows

Continue script execution no matter whether some try fails or not (finally)

Create a temporary file or directory/folder

Remove unwanted/unnecessary parts from strings in a column of dataframe

Convert dataframe row/column into a comma separated string

Compare string entries/cells/elements of columns in different dataframes

Candidate keywords

Built-ins/Builtins Commands in Python

Build own/customized keyword candidates

Electrical characteristics of MOS capacitor

Count how many empty strings in a list

Semantic clustering

Clustering versus Classification of texts and documents

Clustering of texts

Classification of texts

Classification of groups of texts

(Text and image) contrastive learning

Create a log (log.log) file to monitor script execution

Combine multiple images into a single multi-page image or vice versa

Convert/change the case of all letters/word into uppercase (capital) or lowercase in a list of strings

Compare dates (x days after or before a date), and difference between two dates in days

Convert set into a list and vice versa

Merge dictionaries (update(), **, chain(), ChainMap(), |, |=)

Calculating the area fraction of each circle overlapped (filled with color) by a square grid and build wafer map with integration

Convert strings to number (integers/float)

Trick: Get coordinate difference between mouse positions

Select/skip columns by index in DataFrame without changing the DataFrame itself, and change the order of of the selected columns

Convert all elements of specific column or in entire dataframe into strings

Find repeating patterns in columns, group them as cycles, and column correlations

Find the same elements in columns in two separate dataframes and then merge them

Remove the substring after the first or last character "::" in a given string, or extract the substring between the first and last "::"

Codes: Automation of Mouse Movements and Clicks, and keyboard control (comparison among pyautogui, pygetwindow, pydirectinput, autoit, Quartz, platform, ctypes, uiautomation and Sikuli)

Principle and troubleshooting: Automation of Mouse Movements and Clicks (comparison among pyautogui, pygetwindow, pydirectinput, autoit, Quartz, platform, ctypes, uiautomation and Sikuli)

Create table on pptx with certain rows and columns of strings

Create table on pptx with certain rows and columns in DataFrame

Click a menus of an application

exception KeyboardInterrupt, Raised when the user hits the interrupt key (normally Control-C/ctrl-c or Delete).

Check

Compare (pattern/ratio of) two different columns, check whether column values match in DataFrame

Check whether one column contains number only and another column contains letters only or mixture of numbers and letters in DataFrame

Check the difference between two columns in DataFrame

checkpoint_path

Check if two circles intersect or overlap

Check if rectangles overlap

Check if two lists are same/identical

Check all the imported/current modules/libraries

Model checking

Model Checking Algorithms and Modus Ponens Algorithms

save_checkpoints_steps

Convert a CSV file to an image with one column and another column as x-axis and y-axis, respectively.

CSV Merger with Key-Based Matching and Column P Integration

Column-Based Cell Value Extraction in the Same Row in CSV File

Summary and cheatsheet of command for csv file

Collect the file list in a folder into a csv file

pandas for CSV

Write cvs cells

.to_csv()/.writerow()

pandas.DataFrame.to_csv(): DataFrame.to_csv(path_or_buf=None, sep=',', na_rep='', float_format=None, columns=None, header=True, index=True, index_label=None, mode='w', encoding=None, compression='infer', quoting=None, quotechar='"', line_terminator=None, chunksize=None, date_format=None, doublequote=True, escapechar=None, decimal='.', errors='strict', storage_options=None). Write the contents of the Frame into a CSV file

writerow()/.writerows():: Save data into a CSV file.

Write cell by cell with .loc

Search/print/output the rows: Print the rows if their cell values are greater than a specific value, in the csv file with numbers only; output the rows if the cell value is in a specific range.

Sort a csv file with column: used "key = operator.itemgetter()"

Calculation and data extraction in csv under conditions: Compares with the ones which cannot be used for math calculation, find the maximum in a column

Replace/change to new headers in a csv file

Skip rows and/or columns in csv

Merge/combine two csv files

Split columns and merge in csv: Split columns and then merge the splits in a csv file.

Count the number of lines (rows) and columns in a txt (and a csv) file, count different numbers in each region in a column, count missing or not available values.code

Sort a csv file with column: used "key = operator.itemgetter()"

Calculation in csv: Compares with the ones which cannot be used for math calculation, find the maximum in a column

Replace/change to new headers in a csv file

Skip rows and/or columns in csv

Filters the rows based on the condition of being within n days of today's date

.axes[0] and .axes [1]. for csv.

.sum(): sum and percentage for csv

Count duplicates/occurrence and show unique values in csv files

Search in csv file

Split columns and merge in csv: Split columns and then merge the splits in a csv file

Count the number of lines (rows) and columns in a txt (and a csv) file, count different numbers in each region in a column, count missing or not available values.

Search/print/output the rows: Print the rows if their cell values are greater than a specific value, in the csv file with numbers only; output the rows if the cell value is in a specific range.

for ... in rang() in csv

Guess and check algorithm with a combination of a for loop and an if statement

Sort a csv file with column: used "key = operator.itemgetter()"

Calculation in csv: Compares with the ones which cannot be used for math calculation, find the maximum in a column

datatable.Frame.to_csv(): Write the contents of the Frame into a CSV file. If no path is given, then the Frame will be serialized into a string, and that string will be returned

csv.Sniffer(): The Sniffer class is used to deduce the format of a CSV file. It expects a sample string, not a file

next(): Skip headers in CSV

info(): Print information in CSV

Series.to_csv(): Is a 1-D ndarray with axis labels and writes the given series object to a comma-separated values (csv) file/format

line: Print line by line from a CSV file

DataFrame.equals(): Confirm if the two csv files are the same or not

dialect: string or csv.Dialect instance to expose more ways to specify the file format. To expose more ways to specify the file format

Create a file (e.g. csv, pptx files)

csv.writer(). Return a writer object responsible for converting the user’s data into delimited strings on the given file-like object. csvfile can be any object with a write() method

Count duplicates/occurrence and show unique values in csv files

Split columns and merge in csv: Split columns and then merge the splits in a csv file

Count the number of lines (rows) and columns in a txt (and a csv) file, count different numbers in each region in a column, count missing or not available values

Split columns and merge in csv: Split columns and then merge the splits in a csv file.

Skip rows and/or columns in csv

Print/obtain a specific digit in a number, e.g. in a cell value in csv

Write to a specific cell in a csv file

Mean (average, .mean())/.sum()/maximum(.max())/minimum(.min())/number of non-null values(.count())/.median()/variance(.var())/standard deviation(.std()/pstdev())

Get the csv/pandas cell value with certain condition

Add/insert a column into an existing csv file

Change csv cell value under conditions (e.g. if a cell value is equal to another cell value, then compare the third cell value; if both cell value is the same, then change its value to a value)

Read

csv.reader(): Return a reader object which will iterate over lines in the given csvfile

tupleize_cols: If False (default), write as a list of tuples, otherwise write in an expanded line format suitable for read_csv

DictReader()

pandas.read_table()

pandas.read_csv()

Iterate over rows in a DataFrame/read and print row-by-row (number of columns and rows, df.shape[0]/df.shape[1])

Read columns with numeric values/numbers only in dataframe

Electrical characteristics of the MOS capacitor

Change date/month/year format

Get header/column names from DataFrame

Get the frequency of occurrence of a string in a column DataFrame

Difference/comparison between real mouse click and click from script/program, e.g. Pyautogui

Plot images with certain image size and in color

Plot confidence bands

.bat (batch) files for Command Prompt Windows

Trick: pd.concat() for merging/adding (two) columns

CycleGAN (Cycle-Consistent Adversarial Networks)

Copy a file or all files (with os.mkdir) to save to somewhere (create a directory first if it does not exist)

Remove decimal part in a string with comma

Form a list of strings from an old string with all the 6 digits by removing all special characters or spaces

Class

self and __init__ method in Class

Find the computer name

__str__ method for a class

__add__, __call__, __contains__, __delitem__, __delattr__, __eq__, __enter__, __ge__, __getattribute__, __getnewargs__, __getattr__, __getitem__, __gt__, __hash__, __reduce__, __iadd__, __imul__, __init_subclass__, __index__, __int__, __invert__, __new__, __neg__, __reduce_ex__, __reversed__, __rmul__, __radd__, __rand__, __rdivmod__, __rfloordiv__, __rlshift__, __rmod__, __ror__, __round__,__rpow__, __rrshift__, __rshift__, __rsub__, __rtruediv__, __rxor__, __dir__, __doc__, __divmod__, __iter__, __le__, __lt__, __len__, __ne__, __repr__, __setattr__, __setitem__, __sizeof__, __lshift__, __sub__, __subclasshook__, __str__

Safely use credentials (username and password) in Python project

Convert a sentence/text to a list

Merge columns which contain specific strings

Merge rows/columns of a csv file into an old csv file if the rows/columns are not in the old csv file

Select specific columns from a DataFrame to form a new DataFrame

Output the row into dataframe if the value of the cell in a column contains a specific substring in a csv file (with headers)

Add letter/commas/numbers/characters to the end/beginning of strings in a list

Word cloud visualization

Extract the last column as subdataframe

Convert a floating-point number to exponential format

Apply a formatting function to all cells in a DataFrame

Color the Tables in pptx (PowerPoint)

Color and rotate/vertical text in pptx

Selecting only numeric/number columns, and then select two specific columns for plot

Merge columns with character/symbol Separation

Hide x-axis tick labels (only show some labels) where x values are under certain conditions

Create table with merged cells on pptx

Change the width of the cell in ppt

Highlight the plotted dots uncer certain condition

Only use the first 4 characters in the headers of the table for pptx/dataframe

Embed/hide codes or markers into HTML files

Cheatsheet about headers (column names) in DataFrame

Plot a heatmap with three columns of data

Aggregate duplicates in columns of data

Comparative overview of multivariate statistical methods (Correlation Analysis, Regression Analysis, Factor Analysis, Cluster Analysis, Principal Component Analysis (PCA), Canonical Correlation Analysis, Discriminant Analysis, Path Analysis, Structural Equation Modeling (SEM), Multivariate Analysis of Variance (MANOVA), Analysis of Covariance (ANCOVA) ): purposes, variables, and outputs

Overcoming automation challenges and forward-looking suggestions

.create_sheet('')

from typing import List, Dict

.str.split()

expand=True

rename()

regex=True

sort_values(by=...)

head()

dropna(): Allows the user to analyze and drop Rows/Columns with Null values in different ways.

reset_index()

.groupby('...')['...']

unique()

nunique()

left_index=, right_index=

classification_report

.config()

continue

from pptx.dml.color import RGBColor

.color.

ctrlleft

ctrlright

ctrl

from selenium.webdriver.common.keys import Keys

from selenium.webdriver.common.by import By

.center()

hotkey('c')

Type capital letters

plt.colorbar()

sklearn.cluster.KMeans()

.DataFrame(): .drop(), index, columns, axes, dtypes, size, shape, ndim, empty, T (swap between column and row), values

CNTK

Crowd’s error

cosine similarity/distance

Add padding/black/colored edge to images

Save the text in clipboard to a txt file

Common values in two pandas series

Save contents in the webpages obtained by Google search into a text file

Color in table obtained by matplotlib.pyplot/change background color of cells in table

Locate/find the center/coordinates of a bright (maximum/highest intensity) spot in an image

Median blurring and cv2.medianBlur()

Three dimensional (3D) shapes/structures (e.g. cylinder)

Graphlab Create

Categorical variables

Save the image in clipboard to an image file

Compile model

Colab

Categorical features preprocessing layers

GPUs/CPUs

googlecoursera/console.cloud.google

Categorical bins

tf.constant()

find_element(CSS_SELECTOR, " ")

tf.feature_column.categorical_column_with_identity

Convert

Convert a number type to another

Comparisons

Typical training setup in AI and comparisons of different training libraries

Comparison between Python and C/C++

Data structures (Data science, and comparison between list, tuple, set, dictionary)

Comparison between steps and epochs in TensorFlow

Comparison between iteration algorithm and recursive algorithm: a function repeat itself

Comparison of qualifications and skills between data science manager, engineering and scientist

Comparison between machine learning and human beings

Comparison between strings

Comparison with classical wafer map inspection algorithms

Speed comparison with and without numpy

Comparison between =, ==, .copy() and copy.copy() for "list": changes of "list"

Convert capital alphabet letters/characters to number

Extract three blue, green, red images from a color image or grey image, or convert RGB (color) image into three blue, green, red images

Convert images between formats (e.g. jpg, png, tif)

Print and set file path as a variable (e.g. convert all characters in the pathname to lowercase)

Convert a text file to a string

Find and convert the file time/date and compare with the current time

Libraries used to convert incident documents into numerical vectors

Convert PDF file to text file

Put most code into a function or class

Use __name__ to control execution of the code

Match on images to find and to highlight unsimilar (threshold=0) to identical (threshold=1) regions of an image that match a template with a cross-correlation method

Holidays/Festivals/Vocations (Thanksgiving/Christmas)

Call and then run your own functions and modules in different/other Python files

Automatically review, scroll, click webpage and its link

Positions and colors of mouse/cursor and features

while True, e.g. with the "while True" loop, e,g. it constantly/continuously refreshes actions.

Coordinate at center of features, e.g. images

Skip, remove, extract, use specific columns

Automation of mouse movements and clicks

Create a new presentation

Move the cursor/mouse to the found, similar spots one-by-one

Table of PC/computer/Windows shortcut hotkeys

Table of Chrome shortcut hotkeys

Selection between choices or options

Copy and apply formatting in Word and PowerPoint

Work (read, write, insert and delete rows and columns, and merge and unmerge cells, shift/move cell values) in Excel sheets

Calculation in an Excel Sheet, Style, Bold, and Color

Move the mouse/cursor to the left or right

Get the name of the current/most front window

Bind/link/combined multiple commands to buttons

stopwatch and timing/countering a process

Copy and then store it into memory and it can be pasted for use later (multiple clipboard)

Copy text to Clipboard

Courses/classes for Computer Science

Text classification/sort/prediction, train/test e.g. Youtube spam

Print colored text in Python IDLE's terminal

Copy text into clipboard and then use it immediately (one time clipboard)

matplotlib.pyplot axis/text color (xticks, rotation, xlabel, ylabel, title, fontsize, grid(), legend(), show())

Image matching with cross correlation and overlap of template edge. In this matching process, Normalized cross-correlation with those edge images is performed.

Cross correlation between two images

Cross correlation between two images in any sizes. Multiscaling is used to avoid the issue caused by the different sizes of the template and original image, in order to find match in a original image, namely, the size of template is larger than the original image.

watchdog to look for filesystem changes

Skip, remove, extract, use specific columns

Calibrate and put a scale bar, and draw a line segment on an image

Matrix conversion to image

Calculator of length accuracy in 3D structure

Option/selection/choice methods ("pop-up windows of Yes and No ")

Copy text into clipboard and then you can paste it anywhere

Calculate/pass the arbitrary (any) number of variables or input arguments

Merge/combine two text files into a new text file, add a new line to the beginning of a text file

Create an executable (.exe) file from a Python script

Mixing of using numbers and strings by conversions

Calculators

Numpy: Access the element at the second row, the third entry, access a specific row or a column, access some elements (submatrix), or replace/modify an element in the array, print a transfer of an array, access array under conditions or filtering

Calculations in DataFrame: Add a column, calculate for a new column, delete a column, all the rows with values greater than 30 in "Score A" column

Pint summary of the statistic data, change data format, sort/group columns

Handle NaN value in DataFrame, replace empty cells with ...

Copy text into clipboard and then you can paste it a webpage, text/txt, word or powerpoint file automatically

Count the numbers of uppercase letters, lowercase letters and spaces in a string and then swap the cases of the letters.

Count the times of repeated excutions

Markers (e.g. color cross, scatter, and circles) at specific coordinates with x- and y-axis

Remove letters or characters on either side (both left and right sides) and stops when neither such letters no characters on either side

Creates an image from an colored images after remove the grey components (image conversion from color to gray involved)

Calculate the coordinates of a point in a given rectangle and the distance of a given point to a line

Create images with global, adaptive mean, adaptive Gaussian, binary, trunc, Tozero, and tozero thresholds.

Load/launch images and ColorMixing in DigitalMicrograph

Automation of mouse movements and clicks, and keyboard control

dropdown box/option/selection/choice

Add a new slide into an existing ppt or a created ppt file

Draw lines, elbow connectors and arrows in a ppt

Find the color of a pixel on the screen

Plot curve/chart in pptx

Count and delete slides from ppt

Infinite loops (e.g. stop infinite cycling of opening the same images)

Get maximum and minimum value of column and its index

Find a specific word in a webpage and count occurrences

Web Scraping (save contents from a webpage)

Copy a file to save to somewhere

Get/list immediate subdirectories/subfolders; get only the last part of a path/folder/drive; split a dos path into its components, and then print the list

Read its nthcharacter in a text file

Circular dependencies in Python execution

Launch script from another script using subprocess.run/subprocess.call

Monitor multiple changed of folder and files

Monitor the current folder

Find files with a specific file extension/type or with file names ending with specific characters

Move/copy all files from original folder in a directory to a new directory

top and left for pptx (e.g. align the top-left corner of the image to the center of the slide no matter how the size of the images changes)

Invert the contrasts of black and white images

watchdog with conditioning break

Count how many (number) files and folders in a directory

Find contours in an image and their areas and coordinates

Take a screenshot using a mouse click and drag method

Global access to a local variable inside a function/class from outside of the function/class externally

Calculation with combinations of variables from lists

Get mouse position/coordinates on click

Measure length/distance on an image w/o calibrated bar

Get pixel location/coordinates on an image using mouse click/events

Crop/snip (without opening the image) part of a image with definition by a pixel line (with transparent added portion)

Change/swap values in a list

Modify file path/directory by changing folder names by merging a list

Merge/combine two pptx files into one

Plot distance between points calculated by coordinates

Break/exit/skip a function/code line after a certain time

Classification and algorithms for classification

Binary classifiers

Clustering

Count occurrence/nubmer of words/phrase in a text file

Remove/repace (part) character(s) from string

Change/capitalize the case of the first letter of a string

Write/save content to a text file

Generate text file with the bank of collecting all words, characters and strings from news

Critical thinking in data science

Support-vector clustering (SVC)

Model-based clustering

Nearest-neighbor (NN) cluster removal

K-Means clustering for images

Image segmentation ("clustering") in color

Clustering of Laplacian

Mask an image with a threshold or with a color as a threshold

Convolutional neural networks (CNN)

Wafer map failure pattern recognition (WMFPR)/wafer failure pattern detection (WFPD)/defect classification

Convert images between Cartesian and Polar forms

Draw circles/lines on images

Detection and classification of defective dies/chips in wafer map

Convolutional Autoencoder (CAE)

Plot a list of x, y coordinates to an image

Store images in pandas dataframe column

Write contents of DataFrame/memory into text file

Convert DataFrame to a HTML Table and save as a HTML webpage

String template class for formating strings (F-strings (for calculation) (f"{}"), format() method ({}), %s, %d, Template ($))

webdriver.Chrome()

ODBC (Open Database Connectivity)

Access and use SQL Database on SSMS (Microsoft SQL Server Management Studio Express) with pyodbc: localhost, insert rows, update, count updated, delete rows, comparision between extract data by Python and SQL itself

Python drivers for SQL server (pyodbc, pymssql, PyMySQL, cx_Oracle)

Call and run another script in a different/any (parent or children) directory/path/subfolder from a script

Get the current directory/folder path

Change the current directory to any directory/path (e.g. with os.chdir)

Count number of lines in a text file

Find common/different elements/items between two lists/sets

Plot confidence bands

Convert between numpy array and string

igraph for clustering and network

Call/run/execute JMP from Python

Count the number of the pages in a single multi-page/frame image

"@echo off" and "pause" in Command Prompt Window

RegEx (Regular Expression) (characters to check if a string contains a specified search pattern, remove double spaces, and clean texts)

Check ... empty

Check if an item/element is in a list or not

Check if a list is empty or not

Check file existence with partial filename

Check if a file/folder exists or not (Cannot find a specific file/folder? a specific folder in the path? select specific folders to form a string, split a dos path into its components, and then print the list, or check files with extension)

Check if Windows/PC screen is locked

Check if two lists have the same elements

Check whether a file is empty or not

Check if a variable does exist/is assigned/defined

Check if a string is empty or space only

Check if a key exists in a dictionary

'xyz'.isalpha(): Check if string is alphabet (letter, or one type of character)

Check all the imported/current modules/libraries

Check if one list is subset of another (partially (part of))

Check if a variable is a number or string

Check if an element in a sublist of a list

Check if a file exists again (double check)

Clean clipboard and/or check if clipboard is empty, text or image

Check updated new files in a folder

Check if all the (and how many, length of a string) characters in the text are digits/numbers

Check to see if or get a window with a name containing specific titles or texts

Check the letters and symbols starting and ending with

Keyword search function/check whether or not a string is within another string (a space is included as a string character)

Check if a popup dialog is a window or not for Selenium app

checkbox

Check/find/get a file name or the last folder name (e.g. from a path/directory)

Check if both files are the same file, e.g. symbolic link, shortcut

Check if a letter is in a string

Check if a string can be converted to float

Check if a letter/character is in a string

Extract text/check specific text from multiple powerpoint files

Add a new slide into an existing ppt, or work on existing slides, check the existence of a pptx file, if does not exist then create it

Compare/check if two text files have the same contents

Check existence of phrase on text file line-by-line

from keyboard import is_pressed (Esc, check pressed key)

Check and drop negative from dataframe pandas

Check (difference) whether or not a cell value in a column of a CSV file Matchs a value in a column of another CSV file, then do something: e.g. add a value to another column of a csv file

File name, folder name. {}{}....format. Manipulation of file and folder names (rename file name and folder name): i) Check and create a new folder and then copy all files from a folder to the new folder and rename the file, and then open the file. If the folder exists, then no file will be copied, but the file will still be opened. ii) Print and export the folder names and file names (with or without extensions) from a folder into a text file. iii) csv2image filename.

Check if CSV cell value is NaN

Check if a CSV file contains all of the specified strings

CSV

Convert between rows and columns from csv: Convert resulting row from CSV search into a column.

Convert CSV to images, row-by-row, with pixel values: each row is an image

Heatmap with input from a csv/pkl file

Print all values cell by cell in order of row and column in the csv file

Replace/change to new headers in a csv file

Remove duplicate cell values from a csv file/dataframe (e.g. keeping the first/top one; drop_duplicates(); .duplicated(); .get_option(); .set_option(); keep='first'/keep='last'; display.max_rows; display.max_columns)

Skip rows and/or columns in csv

Data cleaning examples in csv files

Skip/remove empty rows (row-by-row) in DataFrame/csv

Convert a CSV file to a JSON file

csv workflow: Read into dataframe, Select a specific column from DataFrame, Select several specific columns to plot

Change/convert a colored image to a grey image(, and then show pixel values).

cv2, cv2, cv2/skimage. cv2/skimage. PIL. matplotlib.

Convert a CSV file to a TXT file

Multiple headers in a csv file: Count the number of header rows first and then split a single csv file to multiple csv files

Change/rename a column name/header in a CSV file

Delete the column/row in a CSV file if they are empty or less than a number (or header/index only)

Read specific cells (cell by cell) in csv file

Create CSV files (e.g. with headers only)

CSV column transposer (rows/columns)

Input a sentence and then output a sentence based on a dictionary obtained from csv

Creates a dictionary from a csv file

Skip/replace empty cells/NaN value from DataFrame/CSV file

Trick: Output a portion of rows and columns from a csv file cell by cell into another csv file

Write special/certain rows (row-by-row) of one csv file to another csv file

Convert csv/dataframe column to a list or vice versa

Plot graph/figure/image from CSV file/DataFrame by removing/hiding blank/empty cells with axis range (plt.xlim())

Plot graph/figure/image from CSV file

Creates a dictionary from a csv file

Put the keywords in a grouped string into the first available cells in the corresponding columns in a csv file

Separately plot data into the same graph/figure/image from different csv files for each category (import multiple CSV files and concatenate into one DataFrame): append row-by-row or column-by-column

Convert a csv column to a string seperated by comma

cv2.imwrite:: Save images

names: Names in headers of csv files

code. code

.groupby(): sort/group columns.

(code). CSV: (code)

quoting: Set quoting rules as in csv module (default csv.QUOTE_MINIMAL)

cv2.imread(/path/to/image, flag): A method loads an image from the specified file. If the image cannot be read (because of missing file, improper permissions, unsupported or invalid format) then this method returns an empty matrix. imread() decodes the image into a matrix with the color channels stored in the order of Blue, Green, Red and A (Transparency) respectively: (:, :, 0) represents Blue channel; (:, :, 1) represents Green channel; (:, :, 2) represents Red channel; (:, :, 3) represents Transparency channel. The flag is optional.

code. code. code. code.

cv2.IMREAD_GRAYSCALE: Reads the image as grey image. If the source image is color image, grey value of each pixel is calculated by taking the average of color channels. = 0,

code.

DataFrame workflow: Drop/delete rows with empty cells in a column, Sort DataFrame by time/date order

Electrical circuit simulations

NgSpice/PySpice

Switches simulations

Diodes simulations

Plot workflow: Create new empty column in DataFrame, Move the cells in a column to another column under certain condition, Select specific columns for scatter plot

inplace=True

Change the items permanently. (code). (code).

columns=

(code). (code).

delim_whitespace

Parse whitespace-delimited (spaces or tabs) file (much faster than using a regular expression)

compression

decompress ’gzip’ and ’bz2’ formats on the fly. Set to ’infer’ (the default) to guess a format based on the file extension.

dtype

A data type name or a dict of column name to data type. If not specified, data types will be inferred.
(Unsupported with engine=’python’)

header=

Whether to write out the column names (default True). Introduction. (code). Row number(s) to use as the column names, and the start of the data. Defaults to 0 if no names passed, otherwise None. Explicitly pass header=0 to be able to replace existing names. The header can be a list of integers that specify row locations for a multi-index on the columns E.g. [0,1,3]. Intervening rows that are
not specified will be skipped (e.g. 2 in this example are skipped). Note that this parameter ignores commented lines and empty lines if skip_blank_lines=True (the default), so header=0 denotes the first line of data rather than the first line of the file.

skip_blank_lines

whether to skip over blank lines rather than interpreting them as NaN values

skiprows

A collection of numbers for rows in the file to skip. Can also be an integer to skip the first n rows

index_col

column number, column name, or list of column numbers/names, to use as the index (row labels) of the resulting DataFrame. By default, it will number the rows without using any column, unless there is one more data column than there are headers, in which case the first column is taken as the index.

names

List of column names to use as column names. To replace header existing in file, explicitly pass header=0.

true_values

list of strings to recognize as True

false_values

list of strings to recognize as False

keep_default_na

whether to include the default set of missing values in addition to the ones specified in na_values

parse_dates

if True then index will be parsed as dates (False by default). You can specify more complicated
options to parse a subset of columns or a combination of columns into a single date column (list of ints or names, list of lists, or dict) [1, 2, 3] -> try parsing columns 1, 2, 3 each as a separate date column [[1, 3]] -> combine columns 1 and 3 and parse as a single date column {‘foo’ : [1, 3]} -> parse columns 1, 3 as date and call result ‘foo’

keep_date_col

if True, then date component columns passed into parse_dates will be retained in the output (False by default).

date_parser

function to use to parse strings into datetime objects. If parse_dates is True, it defaults to the very robust dateutil.parser. Specifying this implicitly sets parse_dates as True. You can also use functions from community supported date converters from date_converters.py

.to_datetime()

Change data format. (code)

dayfirst

if True then uses the DD/MM international/European date format (This is False by default)

thousands

specifies the thousands separator. If not None, this character will be stripped from numeric dtypes. However, if it is the first character in a field, that column will be imported as a string. In the PythonParser, if not None, then parser will try to look for it in the output and parse relevant data to numeric dtypes. Because it has to essentially scan through the data again, this causes a significant performance hit so only use if necessary.

lineterminator

string (length 1), default None, Character to break file into lines. Only valid with C parser

quotechar

string, The character to used to denote the start and end of a quoted item. Quoted items can include the delimiter and it will be ignored.

skipinitialspace

boolean, default False, Skip spaces after delimiter

escapechar

string, to specify how to escape quoted data

comment

Indicates remainder of line should not be parsed. If found at the beginning of a line, the line will be ignored altogether. This parameter must be a single character. Like empty lines, fully commented lines are ig-
nored by the parameter header but not by skiprows. For example, if comment=’#’, parsing ‘#emptyn1,2,3na,b,c’ with header=0 will result in ‘1,2,3’ being treated as the header.

.value_counts()

.value_counts(normalize=False, sort=True, ascending=False, bins=None, dropna=True). (code) (code)

skip_footer

number of lines to skip at bottom of file (default 0) (Unsupported with engine=’c’)

confirm()

confirm(text='', title='', buttons=['OK', 'Cancel']) (code)

converters

a dictionary of functions for converting values in certain columns, where keys are either integers
or column labels

encoding

a string representing the encoding to use for decoding unicode data, e.g. ’utf-8‘ or ’latin-1’. Full list of Python standard encodings

verbose

show number of NA values inserted in non-numeric columns

squeeze

if True then output with only one column is turned into Series

error_bad_lines

if False then any lines causing an error will be skipped bad lines

usecols

skip column. Only store the columns which are need so that a subset of columns is returned, resulting in much faster parsing time and lower memory usage. code. code. code. code.

mangle_dupe_cols

boolean, default True, then duplicate columns will be specified as ‘X.0’...’X.N’, rather than ‘X’...’X’

tupleize_cols

boolean, default False, if False, convert a list of tuples to a multi-index of columns, otherwise, leave the column index as a list of tuples

float_precision

string, default None. Specifies which converter the C engine should use for floating-point values. The options are None for the ordinary converter, ‘high’ for the high-precision converter, and ‘round_trip’ for the round-trip converter.

path_or_buf

A string path to the file to write or a StringIO

sep

Field delimiter for the output file (default ”,”)

na_rep

A string representation of a missing value (default ‘’)

float_format

Format string for floating point numbers

cols

Columns to write (default None)

index

whether to write row (index) names (default True)

index_label

Column label(s) for index column(s) if desired. If None (default), and header and index are True, then the index names are used. (A sequence should be given if the DataFrame uses MultiIndex).

mode

Python write mode, default ‘w’

encoding

a string representing the encoding to use if the contents are non-ASCII, for python versions prior to 3

line_terminator

Character sequence denoting line end (default ‘\n’)

quotechar

Character used to quote fields (default ‘”’)

doublequote

Control quoting of quotechar in fields (default True)

escapechar

Character used to escape sep and quotechar when appropriate (default None)

chunksize

Number of rows to write at a time

date_format

Format string for datetime objects

lineterminator

code.

describe()

Print statistic summary of the data. (code)

import pandas as pd

code.

skiprows

code. code. code.

skipfooter

skip rows from bottom. code.

header

skip header. code. code. code. code.

engine

code.

skiprows = lambda x:

code. code. code.

index_col

Skip column index. code. code. code.

.fillna()

Replace empty cells with anything. (code)

drop()

(code)(code)

confusion_matrix

(code). (code)

click()

.click() function is just a convenient wrapper around these two .mouseDown() and .mouseUp() function calls. click() without parameters gives a single, left-button mouse click at the mouse’s current position; click(x, y) calls moveTo() before the click. 'left', 'middle', and 'right' specify a different mouse button. (code)

.clear()

Delete all the dictionary's key-value pairs. General.

__class__

__class_getitem__

clear

copy

__ceil__

__class__

count

conjugate

math.ceil()

The ceiling of a given number is the nearest integer greater than or equal to that number. For example, the ceiling of 4.568 is 5. Code

math.ceil()

math.cos()

math.copysign(x, y)

Copy sign: The sign of the second argument is returned along with the result on the execution of this function. x: Integer value to be converted, y: Integer whose sign is required. Example code

math.cosh()

case_sensitive=True

(code)

Integer/fractions/round /decimal/digits/floating
/ceil/floor

It does not have any fractional part. Introduction. int: Example code.

Complex

It can store real and imaginary parts

Conversions

Cast, or convert a variable from one type to another. Input() always stores a string, even if the value inputted is a number. Casting = temporarily converting a value to another type. There could be loss of precision: i.e. int(1.5) turns it into 1. code.

int()

Converts a float number or a string to an integer, cast the number. code1

float()

Returns a floating point number constructed from a number or string

str()

Introduction. Returns a string which is fairly human readable. code.

"str()" and "," difference

(code)

chr()

Convert an integer to a string of one character whose ASCII code is same as the integer. Introduction.

complex()

Print a complex number with the value real + imag*j or convert a string or number to a complex number

ord()

Returns an integer representing Unicode code point for the given Unicode character. code. code

hex()

Convert an integer number (of any size) to a lowercase hexadecimal string prefixed with “0x”

oct()

Convert an integer number (of any size) to an octal string prefixed with “0o”

.convert()

Image.convert(mode=None, matrix=None, dither=None, palette=0, colors=256). Dither: Dithering method, used when converting from mode “RGB” to “P” or from “RGB” or “L” to “1”. Available methods are NONE or FLOYDSTEINBERG (default). code. code.

capitalize()

(Code) Returns a copy of the original string and converts the first character of the string to a capital (uppercase) letter while making all other characters in the string lowercase letters. code. code.

os.chdir

code

ctypes

Code. Code.

ctypes.windll.user32.MessageBoxW

Code. Code.

shutil.copyfileobj

code.

shutil.copy()

(code)

.correlate2d

code. code.

Correlate1D()

Performs a 1D correlation using Fourier transforms.

Correlate2D

Performs a 2D correlation using Fourier transforms and uses ft.fft2d and ft.ifft2d.

Correlate2DF

Can be is used in cases where the input and filter are already in Fourier space, and can also be used to finish the correlation computation between the inputs and
filter. Code.

conjugate( )

Code.

ConfigParser

Manipulate data and manage user-editable configuration files for an application. The configuration files are organized into sections, and each section can contain name-value pairs for configuration dat

scipy.linalg.circulant

Create a circulant matrix.

scipy.linalg.companion

Create a companion matrix.

scipy.linalg.convolution_matrix

Create a convolution matrix.

linalg.cholesky(a)

Cholesky decomposition.

linalg.cond(x[, p])

Compute the condition number of a matrix.

command

Introduction. code. code.

cmap=plt.cm.gray

code.

__call__/method-wrapper

name/type: implementation of the () operator; a.k.a. the callable object protocol

__closure__/tuple

name/type: the function closure, i.e. bindings for free variables (often is None)

__code__/code

name/type: function metadata and function body compiled into bytecode

skimage.measure.compare_mse(im1, im2)

Compute the mean-squared error between two images.

skimage.measure.compare_nrmse(im_true, im_test)

Compute the normalized root mean-squared error (NRMSE) between two images.

skimage.measure.compare_psnr(im_true, im_test)

Compute the peak signal to noise ratio (PSNR) for an image.

skimage.measure.correct_mesh_orientation(...)

Correct orientations of mesh faces.

skimage.measure.CircleModel()

Total least squares estimator for 2D circles.

compare_ssim(X, Y[, ...]), or skimage.measure.compare_ssim(X, Y[, ...])

Is a function from scikit-image, a score (structural similarity index between the two input images. Compute the mean structural similarity index between two images. This value can fall into the range [-1, 1] with a value of one being a “perfect match”) and difference image can be calculated. code.

import clipboard

(code)

Chainer

Is a competitor to Hebel. It aims at increasing the flexibility of deep learning models. The three key focus areas of chainer include :
a. Transportation system: The makers of Chainer have consistently shown an inclination towards automatic driving cars and they have been in talks with Toyota Motors about the same.
b. Manufacturing industry: From object recognition to optimization, Chainer has been used effectively for robotics and several machine learning tools.
c. Bio-health care: To deal with the severity of cancer, the makers of Chainer have invested in research of various medical images for early diagnosis of cancer cells.

v2.rectangle(image, start_point, end_point, color of border line, border thickness)

border. Compute the bounding box of the contour and then draw the bounding box on an image to represent where the ROI is. code. code. code.

cv2.circle()

cv2.circle(image, center_coordinates, radius, color, thickness). (code). code. code.

cv2.EVENT_FLAG_LBUTTON

Mouse callback function with a single left click. code.

cv2.EVENT_LBUTTONDOWN

Mouse callback function with a single left click. code. (code)

cv2.EVENT_FLAG_MBUTTON

Mouse callback function with a single left click. code.

cv2.EVENT_LBUTTONUP

Mouse callback function with a single left click. code.

cv2.EVENT_LBUTTONDBLCLK

Mouse callback function with double left clicks. code.

cv2.EVENT_RBUTTONDOWN

Mouse callback function with a single right click. code.

cv2.EVENT_RBUTTONUP

Mouse callback function with a single right click. code.

cv2.EVENT_FLAG_RBUTTON

Mouse callback function with a single right click. code.

cv2.EVENT_FLAG_CTRLKEY

Mouse callback function with double right clicks. code.

cv2.EVENT_MBUTTONDOWN

Mouse callback function with the single middle mouse click. code.

cv2.EVENT_MBUTTONUP

Mouse callback function with the single middle mouse click. code.

cv2.EVENT_MOUSEMOVE

Mouse move. code.

cv2.matchTemplate

Introduction. Returns a correlation map, essentially a grayscale image. Other than contour filtering, matching keypoints, contour detection and processing (with thresholding, edge detection, etc. to generate a binary image), template matching is arguably one of the most simple forms of object detection (only 2-3 lines of code), which can detect multiple instances of the same/similar object in an input image. This method quickly fails when there are unknown changes of rotation, scale, viewing angle, etc. In those cases, you should use dedicated object detectors including HOG + Linear SVM, Faster R-CNN, SSDs, YOLO, etc. code. code. code. code. code.
Limitations: The matching can fail (if there is no special treatments in the script) if the size of the template is substantially smaller than the feature in the image being searched.

cv2.Canny()/Canny filter

Introduction. Canny Edge Detection is a popular edge detection algorithm. This detection is susceptible to noise in the image, so that first step is to remove the noise in the image with a 5x5 Gaussian filter. Code. code. code.

cv2.TM_SQDIFF()

cv2.TM_SQDIFF_NORMED

cv2.TM_CCORR

cv2.TM_CCORR_NORMED

cv2.TM_CCOEFF_NORMED()

The third parameter here is the method used for matching. code, code. code.

cv2.TM_CCOEFF

cv2.add

code.

cv2.resize

Resizing does only change the width and height of the image. code.

cv2.waitKey(0)

Will display the window infinitely until any keypress (it is suitable for image display). Therefore, if you use waitKey(0) you see a still image until you actually press something. code. code. code. code.

cv2.setMouseCallback

Mouse clicks: introduction. code. code.

cv2.destroyAllWindows()

Simply destroys all the windows we created. code. code.

cv2.destroyWindow()

To destroy any specific window with the exact window name.

cv2.imshow

A method is used to display an image in a window. The window automatically fits to the image size. First argument is a window name which is a string. Second argument is our image. code. code. Code.

cv2.cvtColor()

Is used to convert an image from one color space to another. code.

cv2.COLOR_BGR2GRAY

code.

cv2.THRESH_BINARY

If pixel intensity is greater than the set threshold, value set to 255, else set to 0 (black). code. code

cv2.THRESH_BINARY_INV

Inverted or Opposite case of cv2.THRESH_BINARY. code. code

cv2.line()

Draw a line in a image. code

cv2.arrowedLine()

cv2.arrowedLine(image, start_point, end_point, color[, thickness[, line_type[, shift[, tipLength]]]]) is used to draw arrow segment pointing from the start point to the end point. The parameters of the cv2.arrowedLine function are the same as those for cv2.line. code.

cv2.putText()

cv2.putText(image, text, org, font, fontScale, color[, thickness[, lineType[, bottomLeftOrigin]]]) is used to draw a text string on any image. The font types are FONT_HERSHEY_SIMPLEX = 0, FONT_HERSHEY_PLAIN = 1, FONT_HERSHEY_DUPLEX = 2, FONT_HERSHEY_COMPLEX = 3, FONT_HERSHEY_TRIPLEX = 4, FONT_HERSHEY_COMPLEX_SMALL = 5, FONT_HERSHEY_SCRIPT_SIMPLEX = 6, FONT_HERSHEY_SCRIPT_COMPLEX = 7, and FONT_ITALIC = 16. The thickness of the line is in pixel. lineType: This is an optional parameter.It gives the type of the line to be used. bottomLeftOrigin: This is an optional parameter. When it is true, the image data origin is at the bottom-left corner. Otherwise, it is at the top-left corner. code. (code)

cv2.namedWindow

code.

cv2.moveWindow

Set the position (coordinates) of the opened window. code.

cv.THRESH_TRUNC

If pixel intensity value is greater than threshold, it is truncated to the threshold. The pixel values are set to be the same as the threshold. All other values remain the same. code. code

cv.THRESH_TOZERO

Pixel intensity is set to 0, for all the pixels intensity, less than the threshold value. code. code

cv.THRESH_TOZERO_INV

Inverted or Opposite case of cv2.THRESH_TOZERO. code. code

v2.rectangle(image, start_point, end_point, color of border line, border thickness)

border. Compute the bounding box of the contour and then draw the bounding box on an image to represent where the ROI is. code. code. code.

Get dimensions (sizes) of image:
dimensions = img.shape
Get height, width, number of channels in image
height = img.shape[0]
width = img.shape[1]
channels = img.shape[2]

General, code. code. code. code. code. code.

Split a list into columns

Introduction

Colors

cmaps['Perceptually Uniform Sequential'] = ['viridis', 'plasma', 'inferno', 'magma', 'cividis']
cmaps['Sequential'] = ['Greys', 'Purples', 'Blues', 'Greens', 'Oranges', 'Reds', 'YlOrBr', 'YlOrRd', 'OrRd', 'PuRd', 'RdPu', 'BuPu', 'GnBu', 'PuBu', 'YlGnBu', 'PuBuGn', 'BuGn', 'YlGn']
cmaps['Sequential (2)'] = ['binary', 'gist_yarg', 'gist_gray', 'gray', 'bone', 'pink', 'spring', 'summer', 'autumn', 'winter', 'cool', 'Wistia', 'hot', 'afmhot', 'gist_heat', 'copper']
cmaps['Diverging'] = [ 'PiYG', 'PRGn', 'BrBG', 'PuOr', 'RdGy', 'RdBu', 'RdYlBu', 'RdYlGn', 'Spectral', 'coolwarm', 'bwr', 'seismic']
cmaps['Cyclic'] = ['twilight', 'twilight_shifted', 'hsv']
cmaps['Qualitative'] = ['Pastel1', 'Pastel2', 'Paired', 'Accent', 'Dark2', 'Set1', 'Set2', 'Set3',
'tab10', 'tab20', 'tab20b', 'tab20c']
cmaps['Miscellaneous'] = ['flag', 'prism', 'ocean', 'gist_earth', 'terrain', 'gist_stern', 'gnuplot', 'gnuplot2', 'CMRmap', 'cubehelix', 'brg', 'gist_rainbow', 'rainbow', 'jet', 'turbo', 'nipy_spectral', 'gist_ncar']. code

matplotlib.cbook

(code) (code)

va='center'

code.

Caffe2

Is a Lightweight, Modular, and Scalable Deep Learning Framework. It aims to provide an easy and straightforward way for you to experiment with deep learning.

random.choice()

Randomly select from options. (code)

t.circle()

turtle.circle(radius, extent=None, steps=None). radius – a number; extent – a number (or None); steps – an integer (or None). (code)

.color()

(code)

Collections of geometric shape

(code)

GetKeyState(VK_CAPITAL)

Caps Lock, .press("capslock"). (code).

from pynput.mouse import Controller

(code)

.click(Button.left, x)

x clicks of mouse. (code)

.locateCenterOnScreen()

x, y = MySearch_img to get the x- and y-coordinates of centers of the feature. (code)

.getAllTitles()

Get all the Python program windows, *IDLE Shell window, e.g. *IDLE Shell 3.9.5, the most front window on Dreamweaver, the most front webpage on each Chrome window, the name of each opened applications, e.g. DigitalMicrograph. Introduction

confidence=

(code), (code), (code).

.configure()

(code)

.copy()

Copy text. (code)

CountVectorizer()

Introduction. It is the bag of words technique, which means counting how many times each word appears and puts them into a vector.

cross_val_score

(code).

from collections import defaultdict

(code).

CBW model (for training)

(code)

driver.current_window_handle

Inches, Emu, Cm, Mm, Pt, and Px are base class for length classes, providing properties for converting length values to convenient units.

.pixelMatchesColor()

Introduction

from pptx.chart.data import ChartData: ChartData()

(code)

.categories

(code)

.chart

(code)

bokeh.plotting.figure.circle()

The circle() function in plotting module of bokeh library is used to Configure and add Circle glyphs to a figure.
Syntax: circle(x, y, *, angle=0.0, angle_units=’rad’, fill_alpha=1.0, fill_color=’gray’, line_alpha=1.0, line_cap=’butt’, line_color=’black’, line_dash=[], line_dash_offset=0, line_join=’bevel’, line_width=1, name=None, radius=None, radius_dimension=’x’, radius_units=’data’, size=4, tags=[], **kwargs)
Parameters: This method accept the following parameters that are described below:
x: This parameter is the x-coordinates for the center of the markers.
y: This parameter is the y-coordinates for the center of the markers.
angle: This parameter is the angles to rotate the markers.
fill_alpha: This parameter is the fill alpha values for the markers.
fill_color: This parameter is the fill color values for the markers.
line_alpha: This parameter is the line alpha values for the markers with default value of 1.0 .
line_cap: This parameter is the line cap values for the markers with default value of butt.
line_color: This parameter is the line color values for the markers with default value of black.
line_dash: This parameter is the line dash values for the markers with default value of [].
line_dash_offset: This parameter is the line dash offset values for the markers with default value of 0.
line_join: This parameter is the line join values for the markers with default value of bevel.
line_width: This parameter is the line width values for the markers with default value of 1.
mode: This parameter can be one of three values : [“before”, “after”, “center”].
name: This parameter is the user-supplied name for this model.
tags: This parameter is the user-supplied values for this model.
radius: This parameter is the radius values for circle markers .
radius_dimension: This parameter is the dimension to measure circle radii along.
size: This parameter is the size (diameter) values for the markers in screen space units.
alpha: This parameter is used to set all alpha keyword arguments at once.
color: This parameter is used to to set all color keyword arguments at once.
legend_field: This parameter is the name of a column in the data source that should be used or the grouping.
legend_group: This parameter is the name of a column in the data source that should be used or the grouping.
legend_label: This parameter is the legend entry is labeled with exactly the text supplied here.
muted: This parameter contains the bool value.
name: This parameter is the optional user-supplied name to attach to the renderer.
source: This parameter is the user-supplied data source.
view: This parameter is the view for filtering the data source.
visible: This parameter contains the bool value.
x_range_name: This parameter is the name of an extra range to use for mapping x-coordinates.
y_range_name: This parameter is the name of an extra range to use for mapping y-coordinates.
level: This parameter specify the render level order for this glyph.
Introduction

Image overlap.

Code. copy method

Template matching: a technique for finding areas of an image that are similar to a patch (template). Patch are small images with a certain feature. The goal of template matching is to find and/or highlight the patch/template in an image.

Copy methods: b = [*a]; c = a * 1; d = a[:]; "e = []; e.extend(a)"; f = a[0:len(a)]; *g, = a; h = list(a); i = [z for z in a]; "j = [] for item in a: j.append(item)"; a.copy(); "import copy l = copy.copy(a)".

code. code.

Computing equations and formulas with Python

Examples. Numerical integration at code.

Prevent other applications to modify the content until other Python script runs

code.

Choose a file with simple dialog.

Code. code. code. With a default folder: code1 and code2. .

Open webpages in internet browsers (Chrome, Microsoft edge, IE browser)

Introduction

Open an image to file from URL (webpage), then it can be saved in PC (computer)

code, code. open with color changed.

Copy images to a different folder/Save an image in a new folder

code, code. code. code.

Set the output image to zero everywhere except my mask (color filter), and display red, green, and blue (RGB) channels of an image.

code, code.

Compute the difference between two images by using Structural Similarity Index with "pip install --upgrade imutils"

code. code