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ji...@google.com
Hello,
We have already been working on the feature for age and even gender detection in face detection. However there is no ETA yet. Please star this case to follow the updates.
We have already been working on the feature for age and even gender detection in face detection. However there is no ETA yet. Please star this case to follow the updates.
su...@pennywisesolutions.com
Hello,
Is there any progress made on the Gender and Age detection. Could you please let us know if there is any possibility of releasing this feature within 2019.
Is there any progress made on the Gender and Age detection. Could you please let us know if there is any possibility of releasing this feature within 2019.
[Deleted User] <[Deleted User]>
Hi!
Is there any update on this feature request?
Is there any update on this feature request?
sa...@gmail.com
Is there any update on both Age/Gender recognition?
jo...@c.snap.com
I believe that google has stated the following; personally (as someone with gay and transgender friends) I agree with google on this one:
https://venturebeat.com/2020/02/20/google-cloud-ai-removes-gender-labels-from-cloud-vision-api-to-avoid-bias/
Google Cloud AI is removing the ability to label people in images as “man” or “woman” with its Cloud Vision API, the company told VentureBeat today. Labeling is used to classify images and train machine learning models, but Google is removing gendered labels because it violates Google’s AI principle to avoid creating biased systems.
“Given that a person’s gender cannot be inferred by appearance, we have decided to remove these labels in order to align with the artificial intelligence principles at Google, specifically Principle #2: avoid creating or reinforcing unfair bias. After today, a non-gendered label such as ‘person’ will be returned by Cloud Vision API,” a Google spokesperson told VentureBeat in an email.
I think this is a smart move on google's part; I have a friend who was born a woman and presents themself as a man, and that is their right, and google should not be telling people how to look or judging them based on their appearance.
Google Cloud AI is removing the ability to label people in images as “man” or “woman” with its Cloud Vision API, the company told VentureBeat today. Labeling is used to classify images and train machine learning models, but Google is removing gendered labels because it violates Google’s AI principle to avoid creating biased systems.
“Given that a person’s gender cannot be inferred by appearance, we have decided to remove these labels in order to align with the artificial intelligence principles at Google, specifically Principle #2: avoid creating or reinforcing unfair bias. After today, a non-gendered label such as ‘person’ will be returned by Cloud Vision API,” a Google spokesperson told VentureBeat in an email.
I think this is a smart move on google's part; I have a friend who was born a woman and presents themself as a man, and that is their right, and google should not be telling people how to look or judging them based on their appearance.
10...@gmail.com
Any updates in 2022 ?
ma...@gmail.com
Is there any ETA for adding Face Age Predictions to Vision API?
We use Vision API constantly for OCR needs, and AutoML for object detection needs - but now have a new requirement to approve or reject documents based on the age of people pictured in the document. We now have to use the Azure Computer Vision service to achieve this while it is not included in Vision API.
We use Vision API constantly for OCR needs, and AutoML for object detection needs - but now have a new requirement to approve or reject documents based on the age of people pictured in the document. We now have to use the Azure Computer Vision service to achieve this while it is not included in Vision API.
am...@gmail.com
Any updates in 2023?
[Deleted User] <[Deleted User]>
Any progress on this subject?
Description
What you would like to accomplish:
When detecting a face with Google Vision API, instead of only detecting how likely is for the person to be an Adult, detect also approximately the age.
How this might work:
When a face was detected, have another field in the JSON responses with roughly estimated age value.
If applicable, reasons why alternative solutions are not sufficient:
The alternative solution is to use the label "adult": "VERY_UNLIKELY". This is not helpful to determine the age of the detected face.
Other information (workarounds you have tried, documentation consulted, etc):