Text-Detection | Text Detection System with MSER , SWT and Text | Data Manipulation library

I am using vision.enums.Feature.Type.DOCUMENT_TEXT_DETECTION to extract some dense text in a pdf document. Here is my code:

Just started exploring Google Cloud Vision APIs. From their guide:

We are developing a mobile app that will allow users to upload images that will be stored in a GCP bucket. However before saving to the bucket we want to blur out any faces and license plates that may be present. We have been using a call to GCP's Cloud Vision service to annotate the image for faces and this has worked quite well. However license plates annotation has turned out to be more challenging. There is no option to detect license plates specifically but instead we seem limited to text-detection which catches license plates, but also all other text that is in image. This is not what we want.

Any pointers on how we might better narrow down the text-recognition to just license plates?

Here's an example of the Python code we are currently using to detect and gather annotation data for faces and text:

I'm working on a Python project. One of the functionalities i need to create is to be able to detect whether an image has text. I do not need any kind of bounding box, I only need true or false, regardless the amount of text the image has. I've been following the steps here but, as all the links i managed to found, it eventually creates the bounding boxes.

I have two questions:

1. Is there any text detection mecanism that i can use to detect text without all the overhead of the bounding box process?
2. OpenCV uses a neural net to detect text which is an exteneral .PB file; i need to load it to use the nn. Is there any way to embed this file within the .py file? This would avoid having two files. The idea behind this is to be able to import the .py file and use it as a library, disregarding the .pb file (which is the model that detects text).

Thank you!

I have a input text file as follows, this is saved as 12.txt:

...

One objective of my project is to detect text from the streaming video using AWS Rekognition.

I have been trying to search the AWS documentation. It seems that the AWS allows the developer to extract text from the stored Images only.

See this AWS documentation - detect text in a Image The AWS documentation provides the following code to detect text in Image. This code basically has detect_text API that takes an stored Image from S3 as an input and outputs the detected text from Image.

My question is -- Is there any method to extract text from a streaming video using AWs Rekognition? OR Can I say that it is not possible to extract text from a streaming video using AWS Rekognition currently?

Let me know any methods to address this objective.

I want to save my output data into the text file where each new line is shown in a different row. Currently each row is delimited by \n, I want new lines to be saved in different rows.

I want to extract handwritten text from an application form using Google Vision API's text detection feature. It greatly extracts the handwritten text but gives very unorganized JSON type response, which I don't know how to parse because I want to extract only the specific fields like name, contact number, email, etc. and store them into MySQL database.

Code (https://cloud.google.com/vision/docs/detecting-fulltext#vision-document-text-detection-python):

So I know that google-vision api supports multiple language for text-detection. And by using the code below I can detect english language from image. But according to google I can use the parameter language hints to detect other languages. So where exactly am I suppose to put this parameter in the code below?