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# Check Image Deduplication API
- Draft April 13, 2019
- Specs from "VFRAME - SHARED Image Matching - Checkpoint Spec 2019APR.odt"
The VFRAME/Check image deduplication API will provide capabilities to determine if a query image matches any of prior submitted query images.
Functional Requirements:
- provide matching results for at least 10,000 image requests submitted per day
- provide scalable capacity for sustained usage of at least one year
- provide an authenticated API service to match a query image to all previously submitted query images and receive a match result
## Use Case Scenario
User story:
- Audience member sends image to a number on WhatsApp (or generically, user adds an image to Check). - Handled by Smooch.
• Image is ingested into Check. - Handled by Smooch & Check.
• Image is matched against existing images in Check.
◦ MVP:
▪ detect near-identical matches that are different sizes, resolutions.
◦ Assess for feasibility:
▪ find same meme images used for different claims
▪ find same claims using different meme images
▪ find same images (not memes) with different text
▪ find same images + text in different physical files
• Image is automatically related to any matching images in Check.
• Analyst can confirm matches and dissociate any false matches. - Handled in Check
• Audience member receives the verification result for any matching images with existing final-status. - Handled in Check, Smooch, and WA Business API
## Out of Scope
- Video matching
- Machine vision or content analysis
- Indian-language OCR (though OCR models/ libraries should be easily integrated)
- User-in-the-loop machine learning for improvement of matching algorithms
## Example Requests
Example response for a successful image upload with no match:
`check.vframe.io/v1/match/`
```
{
"success": True,
"match": False,
"closest_matches":
[
{
"sha256: "cf80cd8aed482d5d1527d7dc72fceff84e6326592848447d2dc0b0e87dfc9a90",
"score": 2
},
{
"sha256: "156350ca18fa04545c4192432860c7efe9ddba18ea6e40e4da81bb7097a7166f",
"score": 3
}
]
"
```
Example response for a successful image upload with a match:
`check.vframe.io/v1/match/`
```
{
"success": True,
"match": True,
"match":
{
"sha256: "eadc688cd557ee351fa9b718e87a6e8dfb9c9fce69e9944c71c0f58f8b972632",
"score": 0
},
"close_matches":
[
{
"sha256: "cf80cd8aed482d5d1527d7dc72fceff84e6326592848447d2dc0b0e87dfc9a90",
"score": 2
},
{
"sha256: "156350ca18fa04545c4192432860c7efe9ddba18ea6e40e4da81bb7097a7166f",
"score": 2
}
]
"
```
Get match, but with more permissive threshold
`check.vframe.io/v1/match/threshold/3/`
```
{
"success": True,
"match": True,
"matches":
{
"sha256: "eadc688cd557ee351fa9b718e87a6e8dfb9c9fce69e9944c71c0f58f8b972632",
"score": 0
},
"closest_matches":
[
{
"sha256: "cf80cd8aed482d5d1527d7dc72fceff84e6326592848447d2dc0b0e87dfc9a90",
"score": 3
},
{
"sha256: "156350ca18fa04545c4192432860c7efe9ddba18ea6e40e4da81bb7097a7166f",
"score": 3
}
]
"
|
