There is a great site of labs by Oracle - LiveLabs. They are using OCI (Oracle Cloud Infrastructure). One of the labs, named "Build AI-Powered Image Search into your Oracle APEX App" is combining APEX with AI - Vision Service and uses the IMAGE_CLASSIFICATION option of the service.
I already wrote a post about replacing the default Image Classification option of the Vision service with Text Detection here (and did a little journey to understand better the Lab.)
This time I needed to use the Object Detection option of Vision Service.
So I will explain the small changes needed to be done in the original Lab and next talk a bit about the difference between Object Detection and Image Classification.
In the picture there are the various options of AI - Vision Service:
All we have to do are 2 small changes:
In LAB 3, Task 2 - Invoke the OCI Vision REST Data Source through a Page Process, step 10 change to:
Click FEATURE_TYPE and enter the following (we replace the IMAGE_CLASSIFICATION value):
Under Value :
Type: Static Value
Value: OBJECT_DETECTION
In LAB 3, Task 2 - Invoke the OCI Vision REST Data Source through a Page Process, step 14 change the PL/SQL Code to (in the "Parse the Response" part):
UPDATE SM_POSTS
SET
AI_OUTPUT = (
SELECT
LISTAGG(obj_name, ',') WITHIN GROUP(
ORDER BY
obj_name
)
FROM
JSON_TABLE ( :P1_RESPONSE, '$.imageObjects[*]'
COLUMNS
obj_name VARCHAR2 ( 100 ) PATH '$.name[*]'
)
)
WHERE
ID = :P1_ID;
Instead of the original:
UPDATE SM_POSTS
SET
AI_OUTPUT = (
SELECT
LISTAGG(obj_name, ',') WITHIN GROUP(
ORDER BY
obj_name
)
FROM
JSON_TABLE ( :P1_RESPONSE, '$.labels[*]'
COLUMNS
obj_name VARCHAR2 ( 100 ) PATH '$.name[*]'
)
)
WHERE
ID = :P1_ID;
What is the difference?
The original feature of the lab -Image Classification, Assigns classes and confidence scores based on the scene and contents of an image.
This post option - Object Detection, Identifies objects and their location within an image along with a confidence score.
Let's see an example. For the following, very simple picture we will get 2 responses:
Image Classification returns: Human arm,Human face,Human hand,Human head,Human nose
Object Detection returns: Helmet,Human face,Person
Here are the 2 JSON files returned:
Image Classification:
{
"labels": [
{
"name": "Human head",
"confidence": 0.9931826
},
{
"name": "Human hand",
"confidence": 0.99312717
},
{
"name": "Human arm",
"confidence": 0.9930545
},
{
"name": "Human nose",
"confidence": 0.99297017
},
{
"name": "Human face",
"confidence": 0.9926239
}
],
"ontologyClasses": [
{
"name": "Human head",
"parentNames": [],
"synonymNames": []
},
{
"name": "Human nose",
"parentNames": [],
"synonymNames": []
},
{
"name": "Human hand",
"parentNames": [],
"synonymNames": []
},
{
"name": "Human face",
"parentNames": [],
"synonymNames": []
},
{
"name": "Human arm",
"parentNames": [],
"synonymNames": []
}
],
"imageClassificationModelVersion": "1.5.97",
"errors": []
}
Object Detection:
{
"imageObjects": [
{
"name": "Helmet",
"confidence": 0.9530024,
"boundingPolygon": {
"normalizedVertices": [
{
"x": 0.332,
"y": 0.1619190404797601
},
{
"x": 0.531,
"y": 0.1619190404797601
},
{
"x": 0.531,
"y": 0.39580209895052476
},
{
"x": 0.332,
"y": 0.39580209895052476
}
]
}
},
{
"name": "Person",
"confidence": 0.8978557,
"boundingPolygon": {
"normalizedVertices": [
{
"x": 0.169,
"y": 0.17541229385307347
},
{
"x": 0.742,
"y": 0.17541229385307347
},
{
"x": 0.742,
"y": 0.9940029985007496
},
{
"x": 0.169,
"y": 0.9940029985007496
}
]
}
},
{
"name": "Human face",
"confidence": 0.8083062,
"boundingPolygon": {
"normalizedVertices": [
{
"x": 0.363,
"y": 0.34182908545727136
},
{
"x": 0.507,
"y": 0.34182908545727136
},
{
"x": 0.507,
"y": 0.5847076461769115
},
{
"x": 0.363,
"y": 0.5847076461769115
}
]
}
}
],
"ontologyClasses": [
{
"name": "Human face",
"parentNames": [],
"synonymNames": []
},
{
"name": "Helmet",
"parentNames": [
"Sports equipment",
"Clothing"
],
"synonymNames": []
},
{
"name": "Person",
"parentNames": [],
"synonymNames": []
},
{
"name": "Sports equipment",
"parentNames": [],
"synonymNames": []
},
{
"name": "Clothing",
"parentNames": [],
"synonymNames": []
}
],
"objectDetectionModelVersion": "1.3.557",
"errors": []
}
