Author: dsgrover

Stephen managed to get the individual component classification accuracy up to around ~85% in testing, and is still in the process of measuring the full circuit accuracy. The size of the dataset has increased to encompass 56 component images, but in terms of file size it is actually still 3 MB, which is what we predicted two weeks ago. In addition to this, because Stephen switched to using BRIEF descriptors, which are only available with opencv-contrib extra modules, this is an added step for the build process of the integration. This week we were able to completely finish integrating the entire project on one codebase. The CV and the phone app are correctly linked to display the circuit that the CV algorithm recommends and the circuit simulator is able to run with the inputs the user provided. All that is left to be done is to parse the output of the circuit simulator and display it on a final page, however this will be less than a day’s work as we have already parsed the output of the CV code which was far more challenging. In addition to this, the display of the circuit has a couple bugs that need to be worked on, but this is also expected to take around a day. Jaden is planning on finishing both these parts by Tuesday. 

Now that most of the integration is finished, Devan is finishing up working on the model for the diode. Once these parts are finished, the project will be completed.

One change that has an associated cost is the memory usage of the dataset file. Stephen created a YML file with feature vectors representing 27 component images that had a size of 1.4 MB. Our ideal dataset size would comprise 54 component images, which would correspond to a YML file size of ~3 MB. This is bigger than our previously anticipated 500 KB size for 50 component images, but because our maximum application size is set as 100 MB, we don’t expect this 2.5 MB difference to be a problem. In addition, there were some changes regarding how the user will input the component values. When showing progress there were concerns of the UI and it being tailored to a younger audience. Now rather than the user clicking on components to input values, they are presented with text of each component name to click on to input values. We expect this will be more user friendly and will cause less confusion.

We also worked a bit on integrating the computer vision and circuit simulator components of our project. Our circuit simulator is now directly able to simulate a circuit from an image generated by the computer vision algorithm. We are still unable to get the computer vision library to build for XCode though, which may mean we will have to use the Intel Mac lab.

Overall we are more behind schedule than we would like, but hope to make this up over next week’s break. Our goal is to have the full integration complete by the time we come back from break, which gives us time to work on final documentation during the first week back. 

We have all developed lots of skills that we did not previously have by working on our application. Stephen had never used computer vision before, Jaden had never coded an iOS app before, and Devan had limited c++ experience. By working on this project, we were able to develop our skills and become better engineers. From a logistical standpoint, we have learned to work well together by giving each other status updates often to mark our progress and make sure we are relatively on track. This also allows us to pass ideas between each other even though our work is very compartmentalized. Planning the gantt chart also helped a lot because we are able to manage our time better and not spend too much time thinking about what to do next after completing a task. 

Stephen made several large changes to the computer vision subsystem in an effort to improve accuracy of classifications so that we can hit our accuracy requirements. Because of this, he did not get to performing benchmark tests to quantify how accurate the system is as of now. The goal for the end of this week was to get 80% accuracy and 90% next  week. As long as by the end of next week Stephen can hit close to the 90% mark, he will remain on schedule. Otherwise, we will have to use some slack until this mark is hit.

Jaden worked on the application’s UI, specifically the value input for components. He was able to get the feature to work in a way where you can tap on each individual component on the circuit and enter in a value. He still needs to figure out how to display these values onto the screen though. Devan worked mostly on trying to integrate diodes into his circuit simulator. This proved to be very challenging because he has to incrementally solve a system of equations in a loop until his solution converges. He is a little behind, but will make this up over Thanksgiving.

Starting next week we’re going to gradually start working on the integration of our subsystems. This means creating bridge files for the C++ classes that Stephen and Devan have created, as well as some other minor details like what was mentioned in last week’s report.We will also start doing unit and integration testing in order to benchmark requirements and make further refinements.

 

We are on schedule with our progress. This week we finished developing our subsystems so that we are ready for the demo next week. Stephen finished converting the Python proof of concept to C++ code, and has developed a functional example of the computer vision system that he will show during the presentation. Jaden was able to finish debugging the phone application and is now able to display the circuit components with coordinates with a sliding page model. Devan was able to correctly simulate circuits that contain voltage sources, current sources, and resistors. Therefore, we now have each individual subsystem working at a basic level to show for the demo next week.

For the coming weeks we plan to start integrating the subsystems. We expect integrating the phone application and the computer vision code to take time and involve debugging. Therefore, before making further advancements on each subsystem our priority is to integrate and test the subsystems as one system. It should not be too tough to integrate the simulator with the application because the simulator has been developed within the build environment for the application. This means we already know the code to simulate circuits can be built and run on an iOS device like we intended. We are currently on track with the schedule we have planned.

There have been no major changes this week. The system and schedule are still the same, however there were a couple problems with the phone application this week. There is a bug creating the pages to display the circuit and was not resolved due to the ethics assignment taking up a lot of time. The frontend components were created, however they are not displaying on the sliding page correctly given coordinates. This is not a significant risk as this bug should be resolved within a day, however if it continues to persist into next week we plan to implement a different way to display the images instead of a sliding page. This would most likely be individual pages rather than just one. Even with this bug no changes are made to the schedule because the phone application should be able to display full circuits by next week given coordinates. Everything else is still on track.

We also got some bugs when trying to port the python code over to C++ this week. Thus far, all of the computer vision algorithms have been written in Python. Since our application is an iOS application, we will need to switch it to C++ code to build for iOS. We also made some progress on the netlist parsing for the circuit simulator. We now have an algorithm to parse through the netlist and are trying to generate the matrices using the Eigen library we installed last week.