When I am trying to create second after one already created some feature is not highlighted in AWS saasBoost.can anyone help how can i create 2 service and deploye 2 application on saasboost.
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When attempting to create a new GCP VM on a new account, the list of public images is empty. If I try to launch an image from the public marketplace, the boot device will not be attached.
What am I doing wrong here?
Turns out the problem was caused by the security group in my organization which set a public image constraint and neglected to ensure my team was aware of it.
https://cloud.google.com/compute/docs/images/restricting-image-access
open cloud shell as per my comment (right upper corner square with ">" sign)
list images using
gcloud compute images list
Output will look like this:
try to create your VM with desired image via opened cloud shell using for example the following
gcloud compute instances create test --image-family ubuntu-1804-lts --image-project ubuntu-os-cloud
Output should look something like this:
If so, you will find your instance running under compute engine.
PS.
Dont forget to turn these VMs off when you are done.
If you want to select another image make sure to use image project and image family from output from step 2.
Either way at least this should give you some errors to resolve
I'm using AWS Rekognition to perform single-class object detection. I'm assigning image-level labels with only one label in my entire dataset.
This is based on a new feature released by AWS,
https://aws.amazon.com/about-aws/whats-new/2020/06/amazon-rekognition-custom-labels-now-supports-single-object-training/
I have created my dataset with the following configuration.
When I Train my model, my model fails with the following status message,
The manifest file has too few usable labels.
Any ideas on what I might be missing?
The minimum unique label count for the object location (bounding box / detection) use case is 1 label, but the minimum label count for "Objects, Scenes, and Concepts (classification)" i.e. image-level data is 2. If you were auto-assigning image level labels and there was only 1 label assigned, this is likely why you were getting the "manifest file has too few usable labels" error.
Source: https://docs.aws.amazon.com/rekognition/latest/customlabels-dg/limits.html
We would also like to invite users of Amazon Rekognition Custom Labels with questions about the service to consider asking your questions on AWS re:Post: https://repost.aws/
Thank you for using Amazon Rekognition Custom Labels.
Christian Dunn
Rolling update for an instance group fails with "Invalid Fingerprint" error message at console. Earlier rollouts had no issues but recently started seeing this error and updates are failing, even a times Instance Group section of console is going unresponsive.
Already tried :
Creating New Image and using it in a new Template for rolling out update in instance group
Appreciate any clues or help.
Thanks
When trying to roll-out an update to my instance group with the "ROLLING RESTART/REPLACE" button, I got a “Invalid Fingerprint” error message in the Notification. This issue might also be caused by the "ROLLING UPDATE" button. (capital letters are shown at the source GCE interface)
My instance group size was set to 1 instance, and I was getting the error:
"Invalid fingerprint"
To solve the problem, I changed the Instance Group size from 1 to 2, and then rolled the update.
After the update was done - I change the group size back to 1.
For documentation purposes, the error looks like this:
Edit the Instance Group (set number of instances) by clicking the edit button:
.. and update the number of instances:
Currently, our Internal Compute Engine team working on the issue, The current workaround is to use the gcloud command which should also fix the issue on the Cloud Console afterwards. you can do a rolling replace using:
gcloud beta compute instance-groups managed rolling-action replace [instance group]
You can find the details of the command at this link. Also, you can keep an eye for complete resolution of the issue at this public issue tracker link where other users field a defect report. I must also mention that Updating Managed Instance Group is a beta feature as of now.
Quick question and this may be a dumb one. I am attempting to use AWS Code Build with an image I've published to Docker Hub. I selected the option to use a custom image, and the the option to look for the image in another location (an external image repo).
I can't seem to figure out how to reference my image in the appropriate format to use it in the other location field.
Any help would be greatly appreciated.
In the "Other location" text box you can enter the image name from DockerHub. For example, simply give "openjdk" or "openjdk:latest" to use https://hub.docker.com/r/library/openjdk/ as the Docker image for your build. Don't put the "docker pull " prefix for your image name is all.
Note that CodeBuild only supports public Docker images from DockerHub today. Private registries are not supported.
Lets say that you published your image in hub.docker.com, and your repo name is gjackson/myrepo, and you want to grab the image tagged latest, you should populate the other location field with docker.io/gjackson/myrep:latest.
I'm finding the right way to use AWS Rekognition service.
My problem is How to verify a person image on multi collections, I'm reading Build Your Own Face Recognition Service Using Amazon Rekognition | AWS Machine Learning Blog from Amazon but cannot find the implementation document for it. My point is Face verification title.
Update 1:
My target is: Using AWS Rekognition to get person's info by their face.
My problem is: How to make AWS Rekognition improves its accuracy when recognizing a face.
What I tried:
Upload multi captured portraits of a person with same ExternalImageID but I'm not sure it works or not.
Finding a way to create Collection for each person, then upload person's portraits to their Collection but I don't how to search a face through multiple Collections.
I'm trying use S3 for storage people's images then using Lambda function to do something that I've not got yet.
Update 2:
What is your input material: Input materials are some people's portrait photo with ExternalImageID is their name (eg: my portrait photo will have ExternalImageID is "Long").
What are you trying to do: I'm trying to get ExternalImageID when I send a portrait photo of a registered person. (eg: with my other portrait photo, AWS has to response ExternalImageID is "Long").
Do you have it working, but it is not recognizing some people? Yes, it's work but sometimes it cannot recognize exactly people.
Please tell us your use-case / scenario and what you are trying to accomplish:
Create an AWS Rekognition collection with sample name (eg facetest).
Register some people with their name is ExternalImageID.
Submit an image to AWS Rekognition API to get ExternalImageID - his name.
Okay, so basically you have it working but it doesn't always recognise the person. I'll assume it does not even list the person in the response, even with a low percentage.
I would recommend adding multiple images of the same person to the Face Collection, specifying the same ExternalImageId for each image. (Use one Face Collection with all people in it, including multiple images of the same person.)
Please note that "If you provide the same image, specify the same collection, and use the same external ID in the IndexFaces operation, Amazon Rekognition doesn't save duplicate face metadata." However, adding different images with the same ExternalImageId should be fine.