# Using Python Code to Solve a Maze on an Image-Supported Maze

How do we solve a maze on an image-supported maze using maze solver algorithms?

To solve a maze on an image-supported maze using maze solver algorithms, we follow these steps:

## Step 1: Load the Image of the Maze and Convert it to a Binary Image

**Load the image of the maze using an image processing library like OpenCV. Convert the maze image to a binary image to differentiate the walls from the paths.**

## Step 2: Define the Starting and Ending Points in the Maze

**Identify the coordinates of the starting and ending points in the maze. This information is crucial for the algorithm to find the path.**

## Step 3: Create a Matrix to Represent the Maze

**Construct a matrix that represents the maze. Initialize the matrix with the values of the binary image to map out the maze's layout.**

## Step 4: Use a Maze Solver Algorithm

**Select an appropriate maze solver algorithm such as Depth First Search (DFS), Breadth First Search (BFS), or A* algorithm to navigate from the starting point to the ending point in the maze.**

## Step 5: Mark the Path on the Binary Image

**Once the algorithm has discovered the path through the maze, mark it on the binary image. Save the modified image as the output of the solving process.**

## Step 6: Print or Save the Path

**Display the path found by the algorithm on the console for visualization or save it to a file in a readable format for future reference.**