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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


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.


  • 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


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