Data set generation

In the learning so far, I was learning from the state where the dataset was given, so I decided to create the dataset myself. I've collected images of men and women, so I created a dataset from them!

Execution environment

MacOS、Python3.6(anaconda)、VSCode

How to turn an image into a dataset

This is an article that I referred to when creating the dataset this time.

[How to create a dataset from an original image](https://intellectual-curiosity.tokyo/2019/07/02/%E3%82%AA%E3%83%AA%E3%82%B8%E3% 83% 8A% E3% 83% AB% E3% 81% AE% E7% 94% BB% E5% 83% 8F% E3% 81% 8B% E3% 82% 89% E3% 83% 87% E3% 83% BC% E3% 82% BF% E3% 82% BB% E3% 83% 83% E3% 83% 88% E3% 82% 92% E4% BD% 9C% E6% 88% 90% E3% 81% 99% E3% 82% 8B% E6% 96% B9 /)

This time I used 4 image folders. Two men and two women.

To describe the flow of creating this dataset in words ① Take out the files in the image folder one by one and grayscale them. (2) Obtain the index number from which folder you extracted when extracting. ③ Change the grayscale image to your favorite size ④ ** Store in the list in the order of [image, index number of the folder containing the image] **

• This time, the total number was about 400, so the final list contains 800 elements.

Clogged point

When I wanted to retrieve the values listed in (4), I was surprised because I didn't know that if I prepared two variables in the for statement, I could retrieve the data by skipping one.

for feature, label in training_data:

In addition, I will leave it as a memo from here.

os.listdir(A)

You can display the list of files in A.

• If there is a file (B, C, D) in the folder A, you can get B, C, D.

os.path.join(A, B)

You can generate a Path that combines A and B.

cv2.imread('image data')

You can convert image data into an array.

enumerate(Variable name)

When fetching with the for statement, it can be fetched with ** "index number element" **

try:
Conditional expression
except:
   pass 

** Write conditional expression in try + write pass in except = Through even if conditional expression of try comes **

• If this conditional expression is not written, an error will occur.

Finally, I couldn't write in Japanese with matplotlib. Japanese display of matplotlib on Mac With reference to this article, I was able to write in Japanese.

import matplotlib as mpl
matplotlib.rcParams[‘font.family] = ‘AppleGothic’

If you write this code, you can write it in Japanese!

Future issues

This time, I really wanted to cut out only the images of the faces of men and women, but I didn't understand, so for the time being, I created a dataset with the same data.

So, I would like to investigate again to make a data set by including the process of cutting out only the face.

Summary

For the time being, I checked if the datasets were separated and it worked. When I made it myself in this way, I was impressed that I was creating a data set like this, and there were many places to study.