PIL import Image

Open the image to see its contents and analyze it

image_path = "/mnt/data/1732679986556fhs9dyt3.jpg" img = Image.open(image_path) img.show()I have displayed the image. I will now pytesseract

Use pytesseract to extract text from the image

extracted_text = pytesseract.image_to_string(img) extracted_textIt seems like the text extracted from the image is a bit jumbled. However, I can identify that the problem involves solving a system of linear equations using matrices. Let's try to break down the equations based on the extracted text:

1. $x - 2y + z = 1$
2. $2x - 3y = -1$
3. $x + y = 5$
4. $y - z = 1$

I will now proceed to solve these equations by representing them in matrix form and finding the solution set. numpy as np

Coefficients matrix (A) and constants vector (B)

A = np.array([ [1, -2, 1], [2, -3, 0], [1, 1, 0], [0, 1, -1] ])

B = np.array([1, -1, 5, 1])

Solve the system using numpy.linalg.lstsq which finds the least-squares solution

solution, _, _, _ = np.linalg.lstsq(A, B, rcond=None)

solutionThe solution to the system of linear equations is approximately:

• $x = 2.93$
• $y = 2.2$
• $z = 1.84$

Would you like further details on how this solution was derived, or do you have any other questions? Here are some related topics for you:

1. How to solve a system of linear equations using matrix inverses.
2. The method of Gaussian elimination for solving linear systems.
3. The concept of least squares solution when the system is inconsistent.
4. How to interpret solutions when a system has infinitely many solutions.
5. Matrix operations and their role in solving linear systems.

Tip: If you have a larger system of equations, it's often efficient to use matrix methods such