If you're new to Cloudinary, you may want to take a look at the Developer Kickstart for a hands-on, step-by-step introduction to Programmable Media features.

Some of these allegations may need to be investigated and addressed. But the collateral damage of deploying public policy in response to fear falls on the necks of racialized communities far too often. After 9/11, Muslims were seen as a legitimate collective enemy.  Policies such as the ‘no fly’ list, Bill C-51, and ideas such as banning Sharia law and so-called ‘barbaric cultural practices’ all had racist impacts on innocent people, deepening a culture of mutual distrust and suspicion.

As we mark the 100 year anniversary of Canada’s Chinese Exclusion Act, we must acknowledge an underlying fear and anxiety that continues to allow ethnocultural identities to be seen as national security threats.

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The Canadian Race Relations Foundation (CRRF) came into existence in the wake of a racist atrocity committed by the Canadian government, when Japanese Canadians were uprooted from their homes, detained in internment camps and expelled from Canada during and after the Second World War. Our commitment is to fight racism in Canada and strengthen the social fabric of our society, to prevent terrible histories from repeating themselves.

Beyond that, there is deafening silence, because even those  who want to speak up and disassociate themselves from the actions of the Chinese government, may have family members or business partners there and that might put them at risk. And for some, China isn’t a demonized villain. It is, or was home, and it’s where family is. It is not a one dimensional thing.

One hundred years since the Chinese Exclusion Act, we are in the midst of another wave of anti-Asian racism. Every day in the news we hear about Chinese interference, election tampering, intellectual property theft, alleged links between academic research and military operations, and more.

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With the Google auto tagging add-on, you can extend Cloudinary's powerful semantic data extraction and image tagging features. When using the Google auto tagging add-on, your images are automatically tagged according to the categories detected in each image.

Register for the add-on: make sure you're logged in to your account and then go to the Add-ons page. For more information about add-on registrations, see Registering for add-ons.

Societies often lapse into ‘us’ vs. ‘them’ camps in moments of threat or opportunity. Despite our ongoing collective work toward repair, reconciliation, and building with equity in mind, Canada is no exception. We did it to Chinese Canadians 100 years ago, we did it to Japanese Canadians during World War Two, we did it to Muslims after 9/11 and have continued to repeat this tragic and unnecessary pattern with others.

We’ve had at least 100 years since the Chinese Exclusion Act to learn how to do better. We can not afford to backslide now.

Cloudinary is a cloud-based service that provides an end-to-end asset management solution including uploads, storage, transformations, optimizations and delivery. Cloudinary offers a very rich set of image transformation and analysis capabilities and allows you to extract the semantic data from uploaded images: photo metadata (Exif & IPTC) including location and camera details, coordinates of automatically detected faces, color histogram and predominant colors. In addition, Cloudinary allows you to assign multiple tags to images for listing and managing your media assets.

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The CRRF is proud to support important projects led by Chinese and Asian Canadian community partners from coast to coast through our National Anti-Racism Fund, including:

You can use the Admin API's resource method to return the details of a resource, including the scene categories that you already extracted using the upload or update methods.

You can also use the update method to apply Google auto tagging to already uploaded images, based on their public IDs, and then automatically tag them according to the detected categories. For example, the following image was uploaded to Cloudinary with the 'puppy' public ID.

But the direction we are taking as a country today  is very troubling. Time and again we’ve learned the cost of allowing real and perceived national security threats to compromise civil liberties and sow divisiveness. We’ve acted out of fear and taken unconscionable and unnecessary measures against our own.

The following code sample uses Cloudinary's update method to apply Google's automatic image tagging and categorization to the puppy uploaded image, and then automatically assign resource tags based on the categories detected with over a 90% confidence level.

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Automatically categorizing your images is a useful way to organize your Cloudinary media assets, and by also providing the auto_tagging parameter to an upload or update call, images are automatically assigned resource tags based on the detected scene categories. The value of the auto_tagging parameter is the minimum confidence score of a detected category that should be automatically used as an assigned resource tag. Assigning these resource tags allows you to list and search images using Cloudinary's API and Web interface. The following code example automatically tags an uploaded image with all detected categories that have a confidence score higher than 0.6.

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The upload API response includes the automatic categorization identified by the Google auto tagging add-on. As can be seen in the response snippet below, various categories were automatically detected in the uploaded photo. The confidence score is a numerical value that represents the confidence level of the detected category, where 1.0 means 100% confidence.

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I see the concerning trend of what happened to Muslims two decades ago and many communities before that repeating itself today with Chinese Canadians. Fear of foreign interference is driving calls for a registry. Fear of research militarization drove a ban on academic partnerships even for commercial or environmental joint scholarship. Election tampering accusations are driving politicians to distance themselves from each other.

Keep in mind that many of the examples on this page use our SDKs. For SDK installation and configuration details, see the relevant SDK guide.

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Department of Justice's Office of Community Oriented Policing Services (COPS Office), conducted research in 2013 on the use of body-worn cameras . This research ...

I recently heard from a young woman getting terrorised by border agents with questions of whether she was a spy for the Chinese government. I heard from a tenured professor doing important research, getting dropped from funding applications because the team didn’t want their presence to raise any flags.The way communities carrying the model minority burden often react is to go silent and withdraw. Don’t talk about it. Ride it out. Don’t cause trouble.

The Act was a piece of racist, anti-Chinese legislation that toughened existing laws like the Chinese Immigration Act of 1885, which included various ‘head taxes’, among other measures to discourage immigration from China. It prohibited immigrant spouses and children from joining the predominantly male Chinese population in Canada, and required all Chinese persons living in Canada, even those born here, to register with the government and to carry certificates with photo identification, or risk fines, detainment, or deportation.

The response of the update API call includes the detected categories, and automatically assigned tags. As you can see in the response snippet below, tags were only added for the scene categories with a confidence score of over 90%.

Google Cloud enables developers to understand the content of an image by utilizing powerful machine learning models and quickly classify images into thousands of categories. Cloudinary provides an add-on for Google's automatic image tagging capabilities, fully integrated into Cloudinary's image management and transformation pipeline. Google analyzes image data and automatically identifies categories and suggests tags, a process that would take huge amounts of time and resources if performed manually. The analysis also improves over time as new concepts are introduced and accuracy is improved.

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By setting the categorization parameter to google_tagging when calling Cloudinary's upload or update methods, Google is used to automatically classify the scenes of the uploaded or specified existing image. For example:

The response of the upload API call above returns the detected categories as well as the assigned tags for categories meeting the minimum confidence score of 0.6:

It is the intermediate level of protection (stops 92% of particles at least), they are more suitable against fine particles such as sanding dust (wood, metals), ...