How to Detect Text in Images with OCR

Optical Character Recognition (OCR) is a computer vision technique used to identify and recognize text characters in images, with applications across various industries such as inventory management and document digitization. Recent advancements in deep learning have enhanced OCR's performance, although accuracy challenges remain, necessitating error correction strategies. Tools like Roboflow's free OCR API, powered by the machine learning model DocTR, facilitate character recognition in images or videos, offering both hosted and local deployment options for real-time processing. The guide emphasizes the importance of preprocessing and error correction, suggesting techniques like heuristics or spelling algorithms to improve OCR accuracy. Additionally, deploying OCR models on devices through Roboflow Inference is discussed, enabling offline functionality after initial model download. The article exemplifies using Python scripts to run OCR on entire images or specific regions for targeted text extraction, highlighting the need for error correction systems to address model inaccuracies.