Transform your daily workflows and OCR Software Development Progress Report

Aug 6th, 2022
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How to OCR Software Development Progress Report

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throughout your whole career on all projects that you lead youll have to report progress on weekly or monthly basis thats why in this video i will share a simple template for weekly progress report that you can use on any project in any industry after that i will share practical tips and insights from my experience so stay until then [Music] before we get into the details i want you to understand the major concept about the progress reports they are not here to state actually what you did or didnt do or the risks or anything its also not about covering your back if something goes wrong no project reports are the main tool for stakeholder engagement you control stakeholder engagement through things that you report and ask them to do thats why if you dont have any rules or policies in the company youre working in regards to the progress reports i recommend you to keep it simple and follow my recommendations if you do have some established progress report i still recommend you to

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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.
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.
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 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.
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.
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.
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.
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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