HOW OUR MODEL WORKS

We have used YOLO custom-trained model with Tesseract to detect and recognize text within images. Here's a step-by-step explanation of how they work together:

Step-by-Step Process Object Detection with YOLO:

Load YOLO Model: Load your custom-trained YOLO model (best.pt file).

**Detection:**Use the YOLO model to detect objects in the input image. For text detection, the model should be trained to recognize text regions.

Extract Bounding Boxes: YOLO will provide bounding boxes for each detected text region. Image Preprocessing:

Crop Text Regions: For each bounding box detected by YOLO, crop the corresponding region from the original image. These cropped images will contain the text that needs to be recognized.

Optional Enhancements: Preprocess the cropped images to enhance text readability (e.g., binarization, resizing, denoising).

Text Recognition with Tesseract:

OCR on Cropped Images: Apply Tesseract OCR on each cropped image to recognize the text. Tesseract will convert the images of text into machine-readable text. Post-processing: Optionally, clean up the recognized text (e.g., removing special characters, correcting common OCR errors).