SORTING TOMATOES BASED ON SIZE AND COLOR USING TENSORFLOW AND ARDUINO

*** (maximum support duration is up to date 31/12/2019)
A part of abstract:
Thesis uses Raspberry Pi 3 as the main controller to take images of fruits with a camera, forwards the image to a TensorFlow neural network running on a Linux server to perform a more detailed classification of tomatoes has different color, shape, and weight.

We have used the idea from Makoto Koike's project to created our machine.
Makoto Koike's project: https://cloud.google.com/blog/product...
We define 5 types of tomatoes:
Type 1: perimeter greater than 20 cm and ripe red tomatoes completely.
Type 2: perimeter greater than 20 cm and not yet ripe red tomatoes (you know about 70% process to become ripe red)
Type 3: perimeter smaller than15 cm and ripe red tomatoes completely.
Type 4: perimeter smaller than 15 cm and not yet ripe red tomatoes.
Type 5: green tomatoes and things that the machine don't know.
Accuracy rate: 70%.
Materials: Conveyor + Combo Raspberry B+ + Camera + Relay 5V + Power Suppy 12V 5A + Arduino Uno R3 + Servo 9G + ESP8266v1 + Loadcell 5kg + Loadcell HX711 + Mica + Data