In Hasty, we care about your privacy. We want to create an environment that allows you to carry out all the processes – from image annotation to training and inference – within your own infrastructure, and without sharing access to vulnerable data. That’s why we created the Mounting Buckets (MB) feature.
Briefly, it allows you to connect your files from external storages with our platform. The best part is that Hasty does not need to store your files: for us, it is enough to use your images' URLs without direct access to their content. This might be important for users who work with highly-sensitive information and want to eliminate any possibility for others to access the content of their images.
To allow cross-origin access to your bucket, you can apply Cross-Origin Resource Sharing (CORS) rules to it. CORS is a mechanism that allows servers to share restricted resources with other domains by specifying trusted sources (origins).
Hello, thank you for using the code provided by Hasty. Please note that some code blocks might not be 100% complete and ready to be run as is. This is done intentionally as we focus on implementing only the most challenging parts that might be tough to pick up from scratch. View our code block as a LEGO block - you can’t use it as a standalone solution, but you can take it and add to your system to complement it. If you have questions about using the tool, please get in touch with us to get direct help from the Hasty team.
[
{
"AllowedHeaders": [
"Authorization"
],
"AllowedMethods": [
"GET",
"HEAD"
],
"AllowedOrigins": [
"https://app.hasty.ai"
],
"ExposeHeaders": [
"Access-Control-Allow-Origin"
]
}
]
Do not forget to press Save.
Check out the instruction from the AWS if you want to learn more.
1. Create a JSON file with the CORS configuration you want to apply.
An example of CORS configuration:
Hello, thank you for using the code provided by Hasty. Please note that some code blocks might not be 100% complete and ready to be run as is. This is done intentionally as we focus on implementing only the most challenging parts that might be tough to pick up from scratch. View our code block as a LEGO block - you can’t use it as a standalone solution, but you can take it and add to your system to complement it. If you have questions about using the tool, please get in touch with us to get direct help from the Hasty team.
[
{
"origin": ["https://app.hasty.ai"],
"method": ["GET"],
"responseHeader": ["Content-Type"],
"maxAgeSeconds": 3600
}
]
2. Use the gsutil cors
command to apply the configuration to a bucket:
Hello, thank you for using the code provided by Hasty. Please note that some code blocks might not be 100% complete and ready to be run as is. This is done intentionally as we focus on implementing only the most challenging parts that might be tough to pick up from scratch. View our code block as a LEGO block - you can’t use it as a standalone solution, but you can take it and add to your system to complement it. If you have questions about using the tool, please get in touch with us to get direct help from the Hasty team.
gsutil cors set CORS_CONFIG_FILE gs://BUCKET_NAME
Where:
CORSCONFIGFILE
is the path to the JSON file you created in Step 1;BUCKET_NAME
is the name of the bucket you want to provide access to.Visit Google Cloud Storage’s instruction page for more details.
"method": ["GET", "PUT"]
. 1. Please go to your project’s Workspace and click on the External storage access button to create the bucket credentials first. Otherwise, you will have no buckets to get your images from.
2. Press the “Add new bucket” button. Select the credentials title, cloud type, and bucket name. Depending on the cloud storage type, you will need to fill in different fields:
After filling in the bucket credentials, you can access and review them.
3. Go back to your project and click the Images & Datasets tab on the left menu.
4. You will see a small caption under the standard images uploading bar. Click on it to upload the images.
You will have to:
The difference between these approaches is the following:
You can create a dataset using both the Mounting buckets feature and standard image importing.
5. Once the images are uploaded, you can view them in the File manager in the menu on the left.
Congratulations, you have managed to import your data using the Mounting buckets!
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