This week, my team and I have been working on integrating the algorithm with the actual conveyor belt system and getting it to work. To begin with, I switched all of the code to use Numpy, so I got quite a large speedup, so much so that the entire algorithm is now running in around 0.04 seconds, as compared to the earlier 3-4 seconds, so that seems to have worked out well. Next, I instrumented the code in order to better detect when the banana is in the frame, versus when it is coming in, going out, or isn’t in the frame. The edge detection and frame analysis seem to be performing very well. I worked on the final product setup. We just need to place the other camera and the diverter. I have also been testing the conveyor belt system a lot with the algorithm to see how well the image segmentation seems to be performing. There seem to be some issues that are largely resolved with the use of brighter light, so I’ve written code to increase the brightness of the image, but am also looking for a brighter light. When the image is bright, the algorithm seems to be performing very well with the conveyor belt system. Lastly, I worked on coming up with a design for our diverter that will actually divert the fruit on the belt to move into the rotten v/s the fresh fruit basket. We have the CAD design and should be 3D printing it tomorrow. Our plan is that the diverter will extend a bit more into the conveyor belt system so that it can start diverting the fruit much before it actually hits the end of the belt. I tested this using a book to see if it would work, and it seems to be working, so we hope it works out with the 3D printed part!
For future steps, we plan on getting the 3D printed diverter and setting it up with the servo motor so as to see that the diversion is working out well, so I think there’s going to be a lot of testing in the upcoming week. It’s the last leg, so I hope it works out! We also need to write image segmentation code for cucumbers and carrots, but that’s something we plan on looking into after we have the entire system working for a banana since that’s our MVP. The AlexNet classifier isn’t urgent since our classification system seems to be meeting the timing and accuracy requirements extremely well, but I could work on that after we have this setup working. I hope it all works out!