Visual Recognation
Vision AI
Free
Use our game-changing fully managed development environment Vertex AI Vision to create your own computer vision applications or derive insights from images and videos with pre-trained APIs, AutoML, or custom models.
Azure
Free
Boost content discoverability, automate text extraction, analyze video in real time, and create products that more people can use by embedding cloud vision capabilities in your apps with Computer Vision, part of Azure Cognitive Services. Use visual data processing to label content with objects and concepts, extract text, generate image descriptions, moderate content, and understand people's movement in physical spaces. No machine learning expertise is required.
Coming Soon !
import pyodbc
server = '.database.windows.net'
database = ''
username = ''
password = '{}'
driver= '{ODBC Driver 17 for SQL Server}'
with pyodbc.connect('DRIVER='+driver+';SERVER=tcp:'+server+';PORT=1433;DATABASE='+database+';UID='+username+';PWD='+ password) as conn:
with conn.cursor() as cursor:
cursor.execute("SELECT TOP 3 name, collation_name FROM sys.databases")
row = cursor.fetchone()
while row:
print (str(row[0]) + " " + str(row[1]))
row = cursor.fetchone()
"your_database", // update me
"Uid" => "your_username", // update me
"PWD" => "your_password" // update me
);
//Establishes the connection
$conn = sqlsrv_connect($serverName, $connectionOptions);
$tsql= "SELECT TOP 20 pc.Name as CategoryName, p.name as ProductName
FROM [SalesLT].[ProductCategory] pc
JOIN [SalesLT].[Product] p
ON pc.productcategoryid = p.productcategoryid";
$getResults= sqlsrv_query($conn, $tsql);
echo ("Reading data from table" . PHP_EOL);
if ($getResults == FALSE)
echo (sqlsrv_errors());
while ($row = sqlsrv_fetch_array($getResults, SQLSRV_FETCH_ASSOC)) {
echo ($row['CategoryName'] . " " . $row['ProductName'] . PHP_EOL);
}
sqlsrv_free_stmt($getResults);
?>
Amazon
Premium
Automatisez et baissez le coût de votre reconnaissance d'images et de votre analyse vidéo grâce au machine learning
Clarifai
Free
Where developers unleash Production AI with an enterprise-grade Generative AI platform for computer vision & LLMs
curl -X POST \
-H "Authorization: Key YOUR_CLARIFAI_PAT_HERE" \
-H "Content-Type: application/json" \
###############################################################################################
# Initialize the gRPC-based client to communicate with the Clarifai platform.
###############################################################################################
# Import the Clarifai gRPC-based objects needed
from clarifai_grpc.channel.clarifai_channel import ClarifaiChannel
from clarifai_grpc.grpc.api import resources_pb2, service_pb2, service_pb2_grpc
from clarifai_grpc.grpc.api.status import status_pb2, status_code_pb2
# Construct the communications channel
channel = ClarifaiChannel.get_grpc_channel()
# Construct the V2Stub object for accessing all the Clarifai API functionality
stub = service_pb2_grpc.V2Stub(channel)
##############################################################################################
# This is where you set up the metadata object that's used to authenticate.
# This authorization will be used by every Clarifai API call.
# Change the following authorization key to your own credentials
# Example: metadata = (('authorization', 'Key ' + 'a123457612345678'),)
##############################################################################################
metadata = (('authorization', 'Key ' + 'YOUR_CLARIFAI_PAT_HERE'),)
# Or, if you were to use an API Key:
# metadata = (('authorization', 'Key ' + 'YOUR_CLARIFAI_API_KEY_HERE'),)
# Yes, the word 'Key' appears in addition to the alphanumeric PAT or API Key
##############################################################################################
# A UserAppIDSet object is needed when using a PAT. It contains two pieces of information:
# user_id (your user id) and app_id (app id that contains the model of interest).
# Both of them are specified as string values.
##############################################################################################
userDataObject = resources_pb2.UserAppIDSet(user_id='YOUR_USER_ID_HERE', app_id='YOUR_APPLICATION_ID_HERE')
/////////////////////////////////////////////////////////////////////////////////////////////
// Initialize the gRPC-based client to communicate with the Clarifai platform.
////////////////////////////////////////////////////////////////////////////////////////////
// Enable use of the ClarifaiClient object from the Clarifai namespace
use Clarifai\ClarifaiClient;
// Construct the initialization object for accessing all the Clarifai API functionality
$client = ClarifaiClient::grpc();
////////////////////////////////////////////////////////////////////////////////////////////
// This is where you set up the Metadata object that's used to authenticate.
// This authorization will be used by every Clarifai API call.
// Change the following authorization key to your own credentials
// Example: $metadata = ['Authorization' => ['Key a123457612345678']];
////////////////////////////////////////////////////////////////////////////////////////////
$metadata = ['Authorization' => ['Key YOUR_CLARIFAI_PAT_HERE']];
// Or, if you were to use an API Key:
// $metadata = ['Authorization' => ['Key YOUR_CLARIFAI_API_KEY_HERE']];
// Yes, the word 'Key' appears in addition to the alphanumeric PAT or API Key
/////////////////////////////////////////////////////////////////////////////////////////////
// A UserAppIDSet object is needed when using a PAT. It contains two pieces of information:
// user_id (your user id) and app_id (app id that contains the model of interest).
// Both of them are specified as string values.
/////////////////////////////////////////////////////////////////////////////////////////////
use Clarifai\Api\UserAppIDSet;
$userDataObject = new UserAppIDSet([
'user_id' => 'YOUR_USER_ID_HERE',
'app_id' => 'YOUR_APPLICATION_ID_HERE'
]);
Kairos
Premium
Integrate Face Recognition via our cloud API, or host Kairos on your own servers for ultimate control of data, security, and privacy—start creating safer, more accessible customer experiences today.
Imagga
Free
Empowering intelligent apps with our customizable machine learning technology.
# With shell, you can just pass the correct header with each request
curl api_endpoint_here" -H "Authorization: Basic YWNjX2R1bW15OmR1bW15X3NlY3JldF9jb2RlXzEyMzQ1Njc4OQ=="
# Or you can use the user parameter and just specify your api key and secret
curl "api_endpoint_here" --user "<replace-with-your-api-key>:<replace-with-your-api-secret>"
import requests
api_key = '<replace-with-your-api-key>'
api_secret = '<replace-with-your-api-secret>'
response = requests.get(
'https://api.imagga.com/v2',
auth=(api_key, api_secret))
print(response.json())
'<replace-with-your-api-key>',
'secret' => '<replace-with-your-api-secret>'
);
$ch = curl_init();
curl_setopt($ch, CURLOPT_URL, 'https://api.imagga.com/v2');
curl_setopt($ch, CURLOPT_RETURNTRANSFER, TRUE);
curl_setopt($ch, CURLOPT_HEADER, FALSE);
curl_setopt($ch, CURLOPT_USERPWD, $api_credentials['key'].':'.$api_credentials['secret']);
// Some result handling goes here ...
Sightengine
Premium
The perfect tool to automatically moderate content.
Detect and filter any unwanted content in photos,
videos and live streams.
Coming Soon !
from sightengine.client import SightengineClient
client = SightengineClient("{api_user}", "{api_secret}")
output = client.check('scam').set_url('https://d3m9459r9kwism.cloudfront.net/img/examples/example-scam1-1000.jpg')
var sightengine = require('sightengine')("{api_user}", "{api_secret}");
sightengine.check(['scam']).set_url('https://d3m9459r9kwism.cloudfront.net/img/examples/example-scam1-1000.jpg').then(function(result) {
// read the output (result)
}).catch(function(err) {
// handle the error
});
Apiary
Premium
Work together to quickly design, prototype, document and test APIs
curl -X POST \
https://api.cloudsight.ai/v1/images \
-H 'authorization: CloudSight [key]' \
-H 'cache-control: no-cache' \
-H 'content-type: application/json' \
-d '{
"image": "data:image/png;base64,R0lG0dJDAhgbn...etc"
}'
Coming Soon !
Coming Soon !
