nodejs-vision VS berglas

Google also used all of this to improve their OCR algorithms, almost certainly used in Google Cloud Vision[0], but I doubt this was a consideration when deciding if it was transformative/fair use.

0: https://cloud.google.com/vision

You are looking for a computer vision object recognition api, and there are several, all of which cost money. Here are a couple Google’s Microsoft’s

For an example, Google Cloud API which can read images even facial expression and much more and also can differentiate which Image is violating google terms and condition like - pronographic image

tool/software = https://cloud.google.com/vision

I think you’re underestimating how good OCR tech is. Yeah, shitty penmanship will be harder for software to interpret just as it is for the human eye, but legible ink isn’t much of a problem. I just tried scanning my number off my discs and my iPhone digitized it without issue. This technology is essentially made for digitizing handwritten text. Try it yourself if you’d like: https://cloud.google.com/vision

you guys can use this website to extract the japanese texts from the manga pages : https://cloud.google.com/vision/ , then you can google-translate the texts .

Secret Manager: secure storage for sensitive data e.g passwords.

Google Secret Manager

API keys are easy to "leak" or compromise, so best to not only use the restrictions presented to you when you create them but physically protect them as well. Don't code them in plain-text, don't check them into GitHub, etc. Store them in a secure database or use a service like GCP Secret Manager.

I've been looking at Google Secret Manager which sounds promising but I've not been able to find any examples or tutorials that help with the actual practical details of best practice or getting this working. I'm currently reading about Cloud Functions which also sound promising but again, I'm just going deeper and deeper into GCP without feeling like I'm gaining any useful insights.

In this post, I described how to build secure GitHub Actions workflows by pull_request_target event instead of pull_request event. Using pull_request_target, you can prevent malicious codes from being executed in CI. And by managing secrets in secrets management services such as AWS Secrets Manager and Google Secret Manager and access them via OIDC, you can restrict the access to secrets securely. To migrate pull_request to pull_request_target, several modifications are needed. And pull_request_target has a drawback that it's difficult to test changes of workflows, so it's good to introduce pull_request_target to repositories that require strong permissions in CI. For example, a Terraform Monorepo tends to require strong permissions for CI, so it's good to introduce pull_request_target to it.

If you want to make these secrets more secure and get versioning and access logs for them, you may want to switch to Secret Manager later on. They can still be exposed as environment variables to your code. It's a little more setup work, so start with the simple approach at the top.

https://cloud.google.com/secret-manager https://aws.amazon.com/secrets-manager/