Issues:

Decided to give in and try edge impluse. :/

How to classify socks using a Raspberry Pi, Edge Impulse, and balena

messed up and added Lowercase and Uppercase Classes

Fixed

training

half way done

woop woop 95% accurate!

i've ran through the other steps (not pictured)

found this traid off interesteing between ram and runtime speed

First image of raspbery pi cams working! and with ghetto egg conveyor belt ™️!

second picture

getting a training set form the egg conveyor belt

.....

....

Retrying the edgeimpulse + balena cam

Now training the egg classification model

Unfortunitly eggs are much harder to classify 🥺

I only got 71 percent accurancy

Looks like some of the images had had the led light used for candling bleeding over the edge of the egg... :/

These kind of images will cause the model to incorrectly guess

What did i learn today.

1 classifying candled eggs is hard. even for humans!

2 getting good training data is really hard also

3 there are alot of verables that infulces detection

1. setup of camera
2. lighting of scene
3. getting bad data in training set
4. having the egg not lined up to cover the led light

What i could i improve

1. lighting shroud around light
2. bigger training dataset with at least 100 of each example photos with no lens flaired eggs
3. focusing the rpi cam v1 lens, or adjusting distance to its within the focal plane
4. use more camera angle at once
5. retrain using Auto-balance dataset
6. test model with non training set eggs its never seen before
7. get help figuring out why edgeimpluse + balena cam repo doesnt work