High-Accuracy Python OCR Engine

Job ID: 39861956

Budget: $10 – $1,000 USD

I’m sitting on a bank of roughly one million black-and-white images, each a tight 240 × 30 pixels and expected to hold either six or eight digits. The catch is that the digits drift a little in size and position, the backgrounds are less than pristine, and every “obvious” off-the-shelf AI solution I have tried tops out at about 93 % accuracy. I need 99 %.
attached example of pictures

500'000 pictures wil be given to selected candidat
this is not for novice!
on offer please write 500'000 so i know you read spec...


What I’m after is a clean Python program that ingests a single image and returns the full number it contains. From experience, tackling the task digit-by-digit rather than in one sweep gives the best shot, so please architect your approach with that in mind.

You will have access to a sizeable, fully-labeled training set, so there’s no need to build annotations from scratch. Feel free to bring in PyTorch, TensorFlow, Keras, OpenCV or any other Python-friendly tools you deem helpful, provided the final pipeline still meets the 99 % bar on my held-out test batch.

When you deliver, I expect:
• Source code with clear setup instructions
• A trained model (or reproducible training script)
• A short validation report demonstrating ≥99 % digit-level accuracy on unseen data

That’s it—simple to state, challenging to achieve. If you’re confident you can push past that last six percent, let’s talk.