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# app.py
import gradio as gr
from transformers import TrOCRProcessor, VisionEncoderDecoderModel
from PIL import Image
from sympy import sympify, solve, Eq, symbols
# Load the math OCR model and processor
processor = TrOCRProcessor.from_pretrained("nlpai-lab/mathocr-htr-base")
model = VisionEncoderDecoderModel.from_pretrained("nlpai-lab/mathocr-htr-base")
def predict_math_problem(image):
try:
# Transcribe the handwritten math problem
image = image.convert("RGB")
pixel_values = processor(image, return_tensors="pt").pixel_values
generated_ids = model.generate(pixel_values)
transcription = processor.batch_decode(generated_ids, skip_special_tokens=True)[0]
# Standardize mathematical symbols in the transcription
transcription = (transcription
.replace("×", "*")
.replace("÷", "/")
.replace("−", "-")
.replace("√", "sqrt")
.replace("²", "**2")
.replace("³", "**3")
.replace("½", "1/2")
.replace("¼", "1/4")
.replace("…", "...") # Ellipsis
)
# Attempt to solve the mathematical problem
solution = None
try:
# Check if the transcription is an equation (contains '=')
if '=' in transcription:
lhs, rhs = transcription.split('=', 1)
equation = Eq(sympify(lhs.strip()), sympify(rhs.strip()))
variables = equation.free_symbols
if variables:
variable = variables.pop()
solution = solve(equation, variable)
solution = f"{variable} = {solution}"
else:
solution = "No variables found in equation"
else:
# Treat as an arithmetic expression
solution = sympify(transcription)
solution = f"Result: {solution}"
except:
solution = "Invalid or unsolvable expression"
return transcription, solution
except Exception as e:
return f"Error: {str(e)}", "Failed to process"
# Create Gradio interface
demo = gr.Interface(
fn=predict_math_problem,
inputs=gr.Image(type="pil", label="Upload Handwritten Math Problem"),
outputs=[
gr.Textbox(label="Transcribed Text"),
gr.Textbox(label="Solution")
],
title="Handwritten Math Solver",
description="Upload a handwritten math problem to get its transcription and solution."
)
if __name__ == "__main__":
demo.launch() |