I want to build a cloud based solution in which I would give a pool of images; and then ask for "find similar image to a particular image from this pool of images" !! Pool of images can be like "all t-shirt" images. Hence, similar images mean "t-shirt with similar design/color/sleeves" etc.
Tagging solution won't work as they are at very high level.
AWS Rekognition gives "facial similarities" .. but not "product similarities" .. it does not work like for images of dresses..
I am open to use any cloud providers; but all are providing "tags" of the image which won't help me.
One solution could be that I use some ML framework like MXNet/Tensorflow, create my own models, train them and then use.. But is there any other ready made solution on any of cloud providers ?
ibm-bluemix has an api to find similar images https://www.ibm.com/watson/developercloud/visual-recognition/api/v3/#find_similar
Using the Azure Cognitive Services (Computer Vision to be more precise) you can get categories, tags, a caption and even more info for images. Processing all your images would provide tags for your image pool. And that enables you to get similar images based on (multiple) identical tags.
This feature returns information about visual content found in an image. Use tagging, descriptions, and domain-specific models to identify content and label it with confidence. Apply the adult/racy settings to enable automated restriction of adult content. Identify image types and color schemes in pictures.
An example of (part of) a result of the Computer Vision API:
Description{
"Tags": [
"train",
"platform",
"station",
"building",
"indoor",
"subway",
"track",
"walking",
"waiting",
"pulling",
"board",
"people",
"man",
"luggage",
"standing",
"holding",
"large",
"woman",
"yellow",
"suitcase"
],
"Captions": [
{
"Text": "people waiting at a train station",
"Confidence": 0.8331026
}
]
}
Tags[
{
"Name": "train",
"Confidence": 0.9975446
},
{
"Name": "platform",
"Confidence": 0.995543063
},
{
"Name": "station",
"Confidence": 0.9798007
},
{
"Name": "indoor",
"Confidence": 0.927719653
},
{
"Name": "subway",
"Confidence": 0.838939846
},
{
"Name": "pulling",
"Confidence": 0.431715637
}
]
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