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How to OCR Software Development Progress Report

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In this video tutorial, the speaker shares a simple template for creating weekly progress reports applicable to any project across industries. The emphasis is on understanding that progress reports are primarily tools for stakeholder engagement, rather than merely documenting completed tasks or risks. The speaker advises that these reports should facilitate communication and involve stakeholders in the project. For those without established guidelines, a straightforward approach is recommended. Even if established progress reports exist, adherence to the speaker's recommendations is suggested for effective engagement. Practical tips and insights from the speaker's experience will also be shared later in the video.

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How can I improve my Tesseract OCR performance?

OCR accuracy on Unclear image. fix DPI (if needed) 300 DPI is minimum. fix text size (e.g. 12 pt should be ok) try to fix text lines (de-skew and de-warp text) try to fix illumination of image (e.g. no dark part of image) Convert an image into gray scale. Binarize (Gray Scaled) and de-noise image.

How does OCR work step by step?

The OCR engine or OCR software works by using the following steps: Image acquisition. A scanner reads documents and converts them to binary data. Preprocessing. The OCR software first cleans the image and removes errors to prepare it for reading. Text recognition. Postprocessing.

What are the best practices for OCR?

Some General OCR Guidelines The recommended best scanning resolution for OCR accuracy is 300 dpi. Brightness settings that are too high or too low can have negative effects on the accuracy of your image. A brightness of 50% is recommended. Straightness of the initial scan can affect OCR quality.

How to develop OCR software?

How to Create an Optical Character Recognition (OCR) Application? OCR Architecture. Project Organization. The OCR UI (frontend) Commands found in the backend. Accept an Image. Check your credential. Image to Text. Progress. Text to Speech. Code to cloud in 30 seconds.

Why is my OCR not working properly?

If your OCR software is not recognizing text you have scanned, double-check to ensure the image is clear, light, and straight. Make adjustments as needed and rescan your documents. In most cases, this will fix the issue.

What is OCR performance?

Optical Character Recognition (OCR) is a field of machine learning that is specialized in distinguishing characters within images like scanned documents, printed books, or photos. Although it is a mature technology, there are still no OCR products that can recognize all kinds of text with 100% accuracy.

How do I train my own OCR?

Building your own Attention OCR model Gather annotated training data. Get crops for each frame of each video where the number plates are. Generate tfrecords for all the cropped files. Place them in models/research/attentionocr/python/datasets as required (in the FSNS dataset format). Train the model using Attention OCR.

How can I improve my OCR performance?

5 Ways to Improve OCR Accuracy Good Quality of Source Images. Before using OCR, make sure you can read the images with your own eyes. Right Size of Images. Remove Noise / Denoise. Increase Image Contrast. De-skew Original Source.

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OCR Software Development Progress Report