Convert Math Images to Program

Turn screenshots and handwritten formulas into executable Python, MATLAB, or C++.

Image to AlgorithmHigh PrecisionFree & Secure

How to Convert Math Expressions to Code?

01

Upload and Select

Upload your expression image and select 'Math Expression to Code'

02

Start Conversion

Click the "Convert" button to start the conversion process

03

View Result

Once processing is complete, you can view, copy code, or share your results

See the Magic in Action

Upload a math expression image and get executable code in seconds.

Input

Sample math expression

Result

Python
1import math
2
3def solve_quadratic_equation(a, b, c):
4    """
5    Solves the quadratic equation ax^2 + bx + c = 0 using the quadratic formula.
6
7    Args:
8        a: The coefficient of x^2.
9        b: The coefficient of x.
10        c: The constant term.
11
12    Returns:
13        A tuple containing the two roots of the equation, or a message if there are no real roots.
14    """
15    delta = (b**2) - 4*(a*c)
16
17    if delta >= 0:
18        x1 = (-b - math.sqrt(delta)) / (2*a)
19        x2 = (-b + math.sqrt(delta)) / (2*a)
20        return x1, x2
21    else:
22        return "No real roots"
23
24# Example usage (replace with your desired values for a, b, and c):
25# a = 1
26# b = -3
27# c = 2
28# roots = solve_quadratic_equation(a, b, c)
29# print(roots)

This example shows a quadratic equation being converted to a Python function.

AI conversion results may not be 100% accurate. Always review and test generated code before use.

Why use our Math Image to Program Converter?

Rapid Algorithm Implementation

Bridging the gap between theory and practice. Don't waste time manually translating complex paper formulas into code. Upload the equation image, and get a ready-to-run function in seconds. Focus on the logic, not the syntax.

Python & NumPy Optimized

We don't just output generic code; we generate vectorized Python code using NumPy. Our AI understands matrix operations, summations (), and products (), converting them into efficient, high-performance arrays.

MATLAB & C++ Support

Perfect for engineers and simulations. Convert mathematical models directly into MATLAB scripts or C++ functions. Ideal for signal processing, control systems, and numerical analysis tasks.

Handwriting to Function

Snap a picture of your whiteboard brainstorming or notebook scribbles. Our AI recognizes handwritten variables and operators, turning your rough ideas into executable code instantly.

Syntax Error Free

Manual translation often leads to missing brackets or wrong operator precedence. Our AI ensures the generated code follows strict syntactical rules, balancing parentheses and correctly mapping mathematical operators to code equivalents.

Secure Code Processing

We respect your intellectual property. Your mathematical formulas and generated code are processed securely and permanently deleted from our servers shortly after conversion. No data is stored or used for training.

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Frequently Asked Questions

Our system processes mathematical expressions in three steps: First, it recognizes the expression structure and symbols. Then, it converts them into an abstract syntax tree. Finally, it generates optimized, executable code in your chosen programming language.

We support conversion to Python, JavaScript, Java, C++, C#, Go, Rust, Ruby, MATLAB, R, and Julia. The system automatically optimizes the code using appropriate mathematical libraries for each language (e.g., NumPy/SciPy for Python, Math.js for JavaScript).

For most mathematical operations, the generated Python code relies on the standard math library. For matrix operations or complex linear algebra, we generate code optimized for numpy. Make sure to import these libraries (import numpy as np) before running the snippet.

This tool is a Code Generator, not a calculator. It outputs the source code (a function or expression) that implements the formula. You can copy this code into your IDE, define your variables, and run it to get numerical results for any input.

The AI converts summations () into for loops or vector operations (like np.sum), and products () into multiplication loops. For integrals, it generates the code structure for numerical integration (e.g., using scipy.integrate syntax or approximation loops), depending on the complexity.

Common use cases include:

  • Research: Convert mathematical formulas from papers to code
  • Development: Transform equations into optimized implementations
  • Education: Create interactive math demonstrations

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