Machine Learning: Image Classification
task one is image classification. it sounded easy until i started.
This particular taskl was about classification of two sets of data and training the program to know and recognize which data is a car plate number and which is not.
During this process, i gathered images of various car plates both from my partner Google, and the ones i took with my Smartphone. i got some random pictures from my desktop.
I grouped the two data set into folders with different name.
i begand building the classifier with Google Colab, Then imported several python libraries eg: pandas, numpy etc. then i mounted the two data folder into my Google drive for easy assessment.
(this is from statistics)
i used Logistics Regression model which helped to resize all the images. Then I used Logistics regression class from the sklearn module and put the data into the model.
I also created a function that predicts if an image is a plate number or not..
a few challenges i had was lack of regular power supply, Insufficient mobile data.
I encountered a lot of errors; namely os error, fileNameError,