Re: [google-appengine] Re: Image Detection - I want it to look in my library (bucket) only and identify based on images in my own bucket

2018-02-20 Thread Barry Hunter 
Ohh, not seen AutoML before. But yes, that does look like custom trained
AIs hosted in the cloud :)

Interesting.

On 20 February 2018 at 17:04, bFlood  wrote:

> only in alpha now but isn't this what AutoML is suppose to solve? (at
> least the photo based portion, they mentioned there will be other AutoML
> modules). You load your own images, label them and then use the Vision API
> to access the results
>
> https://cloud.google.com/automl/
>
>
>
> On Tuesday, February 20, 2018 at 6:55:18 AM UTC-5, barryhunter wrote:
>>
>> Technically no. You can't upload your own training dataset, and train the
>> AI to produce *your *labels.
>>
>> Would need to deploy your own implementation - possibly via
>> https://opensource.google.com/projects/tensorflow - deployed on GCE
>>
>> https://www.tensorflow.org/tutorials/image_recognition
>>
>> https://cloud.google.com/solutions/running-distributed-tenso
>> rflow-on-compute-engine
>>
>>
>>
>> ... but have had reasonable success building a *second *layer on top of
>> the API, to produce custom labels. Not sure what the proper name is, some
>> sort of Meta-AI.
>>
>>
>> Basically
>>
>> 1) Run all your existing images though the Cloud Vision API, and gather
>> the feature labels it produces.
>>
>> 2) You now have a mapping of 'labels' to your own 'value' - although
>> somewhat fuzzy. Will have a long list of labels for each value. Store these
>> in a database
>>
>> 3) To 'search' images by your "value". first look at the image(s) with
>> that value, and gather all the labels. THen look for the images with the
>> most similar labels.
>>
>> 4) Can also do 'vision lookup' by uploading a image to the Cloud Vision
>> API, and retrieveing a list of labels. Then search your database looking
>> for the images with the most 'similar' labels. Take the 'value from the
>> best match(es).
>>
>>
>> It doesnt matter that what the labels Google AI is detecting on the
>> images, even if nothing like your 'values', just that they similar
>> 'looking'. Say you have a value of 'animal'. The vision api may detect
>> those images as a mixture of differnt animals (cow/dog etc), but you have a
>> mapping back and forth, via your 'training' dataset.
>>
>> Not an AI expert, so probably messing up the terminology, but the labels
>> that Google's AI produces become almost like a set of hidden neurons on
>> your *final *Meta-AI
>>
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[google-appengine] Re: Nodejs Google App Engine Deploy Always Fails - Error Response: [4] Timed out waiting for the app infrastructure to become healthy.

2018-02-20 Thread Oleksandr Oliynyk 
Hello,

yes, let's close this one.

On Tuesday, 20 February 2018 01:38:43 UTC+7, George (Cloud Platform 
Support) wrote:
>
> Hello Alex, 
>
> This is a duplicate of your posting "Google App Engine Deployment Err 
> Debug - Error Response: [4] Timed out waiting for the app infrastructure to 
> become healthy.". You should follow developments on the other thread. It is 
> more effective to concentrate efforts in one place. 
>

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[google-appengine] Re: Google App Engine Deployment Err Debug - Error Response: [4] Timed out waiting for the app infrastructure to become healthy.

2018-02-20 Thread Oleksandr Oliynyk 
Hello George.

Thank you for quick reply. 

Yes, let's keep it in this thread. It is just that I couldn't find anywhere 
my posted issue that I reported it twice.

Best,
Alex

On Tuesday, 20 February 2018 02:02:09 UTC+7, George (Cloud Platform 
Support) wrote:
>
> Hello Alex, 
>
> You have just opened issue 73583699 in the public issue tracker. That 
> posting is richer in information and otherwise the issue tracker offers the 
> advantage of easier follow-up, so I suggest we keep that posting active; 
> all further developments will get reflected in that thread.   
>

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[google-appengine] Re: Image Detection - I want it to look in my library (bucket) only and identify based on images in my own bucket

2018-02-20 Thread bFlood 
only in alpha now but isn't this what AutoML is suppose to solve? (at least 
the photo based portion, they mentioned there will be other AutoML 
modules). You load your own images, label them and then use the Vision API 
to access the results

https://cloud.google.com/automl/



On Tuesday, February 20, 2018 at 6:55:18 AM UTC-5, barryhunter wrote:
>
> Technically no. You can't upload your own training dataset, and train the 
> AI to produce *your *labels. 
>
> Would need to deploy your own implementation - possibly via 
> https://opensource.google.com/projects/tensorflow - deployed on GCE
>
> https://www.tensorflow.org/tutorials/image_recognition
>
>
> https://cloud.google.com/solutions/running-distributed-tensorflow-on-compute-engine
>
>
>
> ... but have had reasonable success building a *second *layer on top of 
> the API, to produce custom labels. Not sure what the proper name is, some 
> sort of Meta-AI.
>
>
> Basically
>
> 1) Run all your existing images though the Cloud Vision API, and gather 
> the feature labels it produces. 
>
> 2) You now have a mapping of 'labels' to your own 'value' - although 
> somewhat fuzzy. Will have a long list of labels for each value. Store these 
> in a database
>
> 3) To 'search' images by your "value". first look at the image(s) with 
> that value, and gather all the labels. THen look for the images with the 
> most similar labels. 
>
> 4) Can also do 'vision lookup' by uploading a image to the Cloud Vision 
> API, and retrieveing a list of labels. Then search your database looking 
> for the images with the most 'similar' labels. Take the 'value from the 
> best match(es).
>
>
> It doesnt matter that what the labels Google AI is detecting on the 
> images, even if nothing like your 'values', just that they similar 
> 'looking'. Say you have a value of 'animal'. The vision api may detect 
> those images as a mixture of differnt animals (cow/dog etc), but you have a 
> mapping back and forth, via your 'training' dataset.  
>
> Not an AI expert, so probably messing up the terminology, but the labels 
> that Google's AI produces become almost like a set of hidden neurons on 
> your *final *Meta-AI
>
>

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[google-appengine] Re: Image Detection - I want it to look in my library (bucket) only and identify based on images in my own bucket

2018-02-20 Thread barryhunter 
Technically no. You can't upload your own training dataset, and train the 
AI to produce *your *labels. 

Would need to deploy your own implementation - possibly 
via https://opensource.google.com/projects/tensorflow - deployed on GCE

https://www.tensorflow.org/tutorials/image_recognition

https://cloud.google.com/solutions/running-distributed-tensorflow-on-compute-engine



... but have had reasonable success building a *second *layer on top of the 
API, to produce custom labels. Not sure what the proper name is, some sort 
of Meta-AI.


Basically

1) Run all your existing images though the Cloud Vision API, and gather the 
feature labels it produces. 

2) You now have a mapping of 'labels' to your own 'value' - although 
somewhat fuzzy. Will have a long list of labels for each value. Store these 
in a database

3) To 'search' images by your "value". first look at the image(s) with that 
value, and gather all the labels. THen look for the images with the most 
similar labels. 

4) Can also do 'vision lookup' by uploading a image to the Cloud Vision 
API, and retrieveing a list of labels. Then search your database looking 
for the images with the most 'similar' labels. Take the 'value from the 
best match(es).


It doesnt matter that what the labels Google AI is detecting on the images, 
even if nothing like your 'values', just that they similar 'looking'. Say 
you have a value of 'animal'. The vision api may detect those images as a 
mixture of differnt animals (cow/dog etc), but you have a mapping back and 
forth, via your 'training' dataset.  

Not an AI expert, so probably messing up the terminology, but the labels 
that Google's AI produces become almost like a set of hidden neurons on 
your *final *Meta-AI

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