how can i use google cloud vision with python django rest api? My task is that i have a picture,i have to find similer picture from an another picture.is there any other solution to do this task?
Here is a simple example app using the google cloud vision API with django. Of course it will take some adapting but it's something to get started with.
Related
I am trying to fetch list of available database versions using google cloud sqladmin API in python.
I am not able to figure endpoint to be used.
Here is rest api doc link.
Can you please guide me how to get solve this?
I want to develop a front-end application for this tutorial: https://www.cloudskillsboost.google/focuses/22020?parent=catalog
Just looking for a simple solution for a user to upload a picture and then the back-end does its processing, thereafter returns the results from the back-end.
Any thoughts or ideas would be much appreciated.
I am trying to deploy an already built image to Cloud Run using .NET Cloud Client Libraries.
I need exactly the same behavior as gcloud run deploy hello --image=us-docker.pkg.dev/cloudrun/container/hello but with .NET Cloud Client Libraries.
Unfortunately, I cannot find an API that does that in https://cloud.google.com/dotnet/docs/reference.
I also tried downloading Cloud SDK from https://cloud.google.com/sdk/docs/install and inspecting the code with PyCharm.
The API is called Cloud Run Admin API.
Cloud Run Admin API
There is an SDK for .NET.
Cloud Run Admin API Client Library for .NET
Namespace Google.Apis.CloudRun.v1
Creating a Cloud Run service is fairly complicated. I recommend that you study the REST API first so that you understand the request body. The .NET library models the REST API.
Method: namespaces.services.create
The key item is the service resource:
Resource: Service
There is a quick way to learn the API request body. Create a simple Cloud Run example and then add the command line option --log-http. Save the output to a file and then study the HTTP request parameters and request body to decipher the very large data structures that are required to create a service.
gcloud run deploy --log-http
I wrote two articles on the Cloud Run Admin API:
Google Cloud Run Deep Dive – Understanding the APIs – Part 1
Google Cloud Run Deep Dive – Understanding the APIs – Part 2
Note: I wrote those articles two years ago. Cloud Run has advanced a lot since then. However, these articles will help you understand the low-level details of the service that were not published elsewhere at the time.
I have just started using GAE and can't figure out how to store images.
I created Django project and deployed on GAE using the methodology in this
tutorial which use cloud SQL (my project uses MySQL)
Now I want to add a Django model for images. I can't figure out how to go about it. I used AWS extensively earlier and stored links in MySQL database while filing on buckets.
Do I need to use google cloud storage? What is the GAE way to do it?
Can any one help me how to access google cloud ml service using Rest API in python. I have tried it using postman but it gives 404 in response everytime.I have some project on google cloud I just want to use all the apis available on https://cloud.google.com/ml-engine/reference/rest/
You can find examples from Datalab:
Training service:
https://github.com/googledatalab/pydatalab/blob/master/google/datalab/ml/_job.py#L61
Prediction service:
https://github.com/googledatalab/pydatalab/blob/master/google/datalab/ml/_cloud_models.py#L225
Alternatively, instead of calling CloudML service endpoints directly, you can try Datalab's ml toolbox itself which supports structured data and image classification. You can view the notebooks first without setting up datalab:
https://github.com/googledatalab/notebooks/tree/master/samples/ML%20Toolbox
To set up Datalab and actually run these notebooks, see https://cloud.google.com/datalab/docs/quickstarts.