Gain insights into using Python for scientific and engineering applications. Delve into real-world scenarios, learning NumPy, Matplotlib, audio processing, and more through practical, hands-on projects.

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jupter.tar.gz

notebook

obesity_plot_gender

print_gender_pandas

create_sine_wave

notebook_exercise

range

print_gender_pandas_remove_NaN

print_gender_year

print_data_age

print_data_age_with_year

print_data_age_remove_NaN

obesity_plot_age_simple

obesity_plot_age_clear

print_data_age_under_16

print_data_age_25_34

obesity_plot_children_vs_adults

print_movie_top_rated

print_movies_oldie_teen

print_movies_by_gender

print_movies_for_women

print_movies_by_gender_loc

print_movies_diff_gender

movies_diff_gender_plot

print_u_data

print_movies_oldie_index

print_movies_oldies

print_movies_teens

display_image_nouse

grey_image

blur_image

edge_detection_low

edge_detection_high

plot_sin_wave

create_wave_file

display_again

print_frequencies

count_objects

detect_faces

detect_faces_little_mix

count_exact_lines

webcam_detection

single_thread

find_correlation

webcam_face_detection

motion_detection

motion_detection_live

In this course, you will learn to use Python for real-world scientific/engineering applications. For each topic, there will be a real case scenario where you will build a quick solution in Python to solve the problem.

More specifically, you will cover topics such as creating a word counter, NumPy and Matplotlib, audio processing, and a lot more. Throughout each chapter, you will get hands-on experience in building solutions for complex problems that engineers and scientists face every day.

The Practical Guide to Python for Scientists and Engineers

# Processing a video frame by frame

OpenCV grabs each frame from a live video via webcam. We’ll use the same processing techniques that we have for a single image. However, this time, we’ll do it frame by frame. This will require a lot of processing.

In the code widget below, we’re creating a face cascade.

In lines 17–18 in the code block below, we captured the video. The read() function reads one frame from the video source, which, in this example, is the webcam. This returns:

* The actual video frame read (one frame on each loop)

* A return code

The return code tells us whether we’ve run out of the frames being read from a file. This doesn’t matter when reading from the webcam, since it can be read forever.

The highlighted piece of code should be familiar as it’s the same one from before. We’re merely searching for the face in our captured frame.

We’ll wait for the "q" key to be pressed in line 45. If it’s pressed, we’ll exit the script.


We’re cleaning up in lines 48–49.



Learn how to detect faces using video in Python.

Extending To a Webcam

Face Detection in Video

Introduction

Create a Word Counter in Python

An Introduction to NumPy and Matplotlib

Python pandas

Audio Processing

Image and Video Processing

MultiThreading vs. Multiprocessing in Python

Machine Learning with an Amazon-like Recommendation Engine

Conclusion

Face Detection in Video

Processing a video frame by frame