CVspice

Goal:

The project CVspice aims to achieve a UI which inputs hand-drawn electric circuits which in turn identifies the components and the nodes which can then be used as an input to LTspice to solve the electrical circuit

Objective:

The UI is split into the following sub-modules:

• Component Recognition & Identification
• Connectivity of Components
• Identification of Nodes

Additionally, we are increasing the the dataset which will also include hand-drawn circuits, and we are exploring OCR for detecting the values of the components directly without the user giving an input.

Method:

• Firstly, Given an electric circuit image, outputs netlist describing components and their corresponding connectivity.
• We have trained around 350 annotated circuit images in YOLOv5 which identifies the circuit components with bounding boxes.
• Terminal points of the circuit components are found by the intersection of the binary image of A-bounding boxes and B- adaptive thresholding of the original image. (A and B) = terminal points
• The nodes of the circuit are found using Breadth-First Search(BFS) algorithm