[SOLVED] html python Skills needed:

Skills needed:
Python 3.4 specify which version used in README file
Python multiprocessing https:docs.python.org3.7librarymultiprocessing.html Python numpy https:numpy.org
Python opencv https:pypi.orgprojectopencvpython
Requirements:
1. Make a python program that runs from the command line python3 YOURSCRIPT.py
2. This main program should spawn three multiprocessing.Process. Do not use threads.
3. In the a.
b.
c. d. e. f. g. h.
main application:
Ask user for the number of random images to generate.
i. Store in multiprocessing.Value named numimages. Ask the user for the dimensions of the image.
i. Store in multiprocessing.Value named height and width.
Create two multiprocessing.Queue named queuea and queueb.
Create one multiprocessing.Array named arraya.
Spawn the three multiprocessing.Process additional instructions below.
Wait for a new image from queueb.
Store the image in arraya.
Allow the user to continue to the next image with ENTER or to quit the program with q.
i. Use multiprocessing.Event named eventquit to signal program completion to the processes.
i.
4. The first process should:
Properly join all processes and cleanly exit.
a. Use numpy to generate an RGB image of a solid color. The color generated should be randomly selected from the following list of RGB colors: black, white, red, yellow, lime, aqua, blue, fuschia
b. After the image is generated it should pass the image to the second process using queuea.
5. The second process should:
a. Wait for a new image from queuea.
b. Inspect the image in order to determine its color. Use only the image data no metadata.
c. After inspecting the image and determining its color, use opencv to watermark the image
with the name of the color. The second process may assume that the color is one of the
colors from the above list.
d. Draw a filled circle of the complementary color opposite on the color wheel in the middle
of the image using a radius of 14 the minimum image dimension. Avoid using for loops to
do this.
e. After watermarking and drawing a circle on the image, place the new image onto a
different queueb.
6. The third process should:
a. Continually read from arraya. Remember that the contents of this array will be updated from the main application.
i. Numpy.frombuffer will be useful for reading and writing this array efficiently. b. Display the image using opencv.imshow.
7. Document all code using python docstrings.
8. Write unit tests for all functions which will be executed by pytest pytest testYOURSCRIPT.py
9. Include a README file. Compress the project directory and include your name in the filename.