Get Token – The token is used for image upload, getting status and getting result for Netra API.

URL: https://api.netra.ai/v1/getToken

HTTP Method: POST

Note: DR – Diabetic Retinopathy

Input

Property	Description
username	Username to access API
password	Password to access API
apiRequestType	DIAB_RETINA = Access DR API

Output JSON

Property	Description
status	200 – Successful 500 – Error in API 411 – API Specific error
token	Token to be used for later transactions. Valid for 2 hours.
remaining	Remaining API Credits
validUpto	Token Valid Until – UTC unix timestamp
message	Message text if there is an error.

Sample Output JSON:

{‘status’: 200, ‘token’: ‘LMoXQtXJ8Y1lJrOYD1O7r5FHPlKWbqgzhwals7scTePBHePdCw8FwZQYgM7k’, ‘remaining’: 100, ‘validUpto’: 1517613274139}

Upload Image For Netra.AI Analysis: Send an image to Netra API for DR Analysis

URL: https://api.netra.ai/v1/doAnalysis

HTTP Method: POST

Conditions:

1. The image should be either of format jpeg or png.
2. The image should be less than or equal to 5 MB.

Input

Property	Description
token	API Token obtained using getToken
image	Base64 format image Data Prepend image information into base64 string For png: data:image/png;base64, For jpeg: data:image/jpeg;base64, Example: data:image/jpeg;base64,/9asdfdsjfdslfeafdsaedd
imageName	Basename of the image to be sent.
bulkImgLabel	Optional – Label to identify a set of images as one group.
imageLocPath	Optional – Path to the file in local machine.

Output JSON

Property	Description
status	200 – Successful 500 – Error in API 411 – API Specific error
jobId	JobId to keep track of the request.
jobStatus	Status of the job when uploaded.
remaining	Remaining API Credits
message	Message text if there is an error.

Sample Output JSON:

1. {‘status’: 411, ‘message’: ‘LC-ERR-0033 : Max Allowed Single Image Size 5 MB.’}
2. {‘status’: 411, ‘message’: ‘LC-ERR-0034 : Only jpeg and png type images allowed.’}
3. {‘status’: 200, ‘jobId’: ‘LaHkZVkSRkHpSdIoA8hgo97BrT47vrZL6FhUX2XqG26RhBxW3luvEjSfAnwPPrR5f2K2xd’, ‘jobStatus’: ‘QUEUED’, ‘remaining’: 43110}

Get Job Status : Get status of your request using jobId.

URL: https://api.netra.ai/v1/getStatus

HTTP Method: POST

Input

Property	Description
token	API Token obtained using getToken
jobId	JobId to for the request.

Output Json

Property	Description
status	200 – Successful 500 – Error in API 411 – API Specific error
jobId	JobId to keep track of the request.
jobStatus	Status of the job when uploaded.
remaining	Remaining API Credits
message	Message text if there is an error.

Sample Output JSON:

a) {‘status’: 200, ‘jobId’: ‘rCSiWGrp4bhOw7AntwlbI9LbaAe2KDIsOb3tvPNoEz2MSF6hW0PumXvGcHTkpVzC4YMjhO’,’statusJob’: ‘QUEUED’’,}

b) {‘status’: 200, ‘jobId’: ‘sk1eD8xw6FfbVLNuuXfTH4UcmguHZrov39mFNG6si071xq7oRdG8r3wKKuaiUlySA8n4Rv’, ‘status’: ‘COMPLETED’}

Get Result for DR Analysis: This will give the result of the DR analysis.

URL: https://api.netra.ai/v1/getResult

HTTP Method: POST

Input

Property	Description
token	API Token obtained using getToken
jobId	JobId for the request.

Output JSON

Property	Description
status	200 – Successful 500 – Error in API 411 – API Specific error
jobId	JobId for the request.
usedOn	Time Used – UTC unix timestamp
usedBy	Used By
statusJob	Status of the request
result	Result of Netra DR Analysis: a) eyeOrNot – Whether image is fundus retina. b) imageQuality – Whether image is gradable. a) drYes – Whether DR present or not. b) referrableDR – Whether Referable DR.
lesionBbox	Lesion info and corresponding bbox data. Bbox format: [x1, y1, x2, y2] Lesions shown: Deep Hemorrhage Drusen Cotton-wool Spot Superficial Hemorrhage Hard Exudate
message	Message text if there is an error.

Sample Output JSON:

a) {‘status’: 200, ‘jobId’: ‘b579a73a688c4dd9beyn3oIeb730057701ec52f7c324db6bf0c9fa01c9527bdETsS7Q’, ‘usedOn’: ‘1516820982075236’, ‘usedBy’: ‘username’, ‘statusJob’: ‘COMPLETED’, ‘result’: ‘{“drYes”:”Detected”,”referrableDR”:”YES”,”imageQuality”:”Gradable Image”,”eyeOrNot”:”YES”}”lesionBbox”:[{“bbox”:”[959,729,1042,812]”,”lesionType”:”Deep Hemorrhage”},{“bbox”:”[795,850,870,932]”,”lesionType”:”Hard Exudate”},{“bbox”:”[524,972,572,1052]”,”lesionType”:”Deep Hemorrhage”}]’}

b) {‘status’: 200, ‘jobId’: ‘8b53d4cfd1ddyc7e226eb0bfab8c889913d60d8af04c4a83b3ecfe50d308a1fbt18tu0’, ‘usedOn’: ‘1514859444682135’, ‘usedBy’: ‘username’, ‘statusJob’: ‘ERROR’, ‘message’: ‘LC-ERR-0035 : Please contact Leben Care Support Team.’}

Sample Code Python: The sample code below does the following:

1. Get Token when username and password are sent and are authenticated.
2. Send an image for DR processing.
3. Ping the api every 90 seconds for the status of the request sent.
4. When the request completes or error is thrown, get the result and display.

 

config_testing.py

fileToProcess=”/path/to/image/sampleRetina.jpeg”;

jobStatusApiUrl=’https://api.netra.ai/v1/getStatus’;

jobResultApiUrl=’https://api.netra.ai/v1/getResult’;

getApiTokenUrl=’https://api.netra.ai/v1/getToken’;

imageUploadApiUrl=’https://api.netra.ai/v1/doAnalysis’;

usernameForGetToken=’username’;

passForGetToken=’password’;

bulkImageLabel=’testLabelBulkImg’;

 

sendImageGetResultForApiDoc.py

import json

import requests

import base64

import os;

import sys;

import mimetypes;

import time;

sys.path.append(os.getcwd());

from config.config_testing import fileToProcess;

from config.config_testing import imageUploadApiUrl;

from config.config_testing import getApiTokenUrl;

from config.config_testing import jobResultApiUrl;

from config.config_testing import jobStatusApiUrl;

from config.config_testing import usernameForGetToken;

from config.config_testing import passForGetToken;

from config.config_testing import bulkImageLabel;

dataForToken = { ‘username’ : usernameForGetToken,

‘password’ : passForGetToken,

‘apiRequestType’: ‘DIAB_RETINA’

};

r_token = requests.post(getApiTokenUrl, data=dataForToken)

dataForToken = r_token.json();

tokenForApi = ”;

if (dataForToken[“status”] != 200) :

print(dataForToken[“message”]);

sys.exit(0);

else :

tokenForApi = dataForToken[“token”];

try :

basenameOfFile = os.path.basename(fileToProcess);

prepend_info = ‘data:%s;base64’ % mimetypes.guess_type(fileToProcess)[0];

with open(fileToProcess, “rb”) as image_file:

imageData = base64.urlsafe_b64encode(image_file.read()).decode(“utf-8”)

imageData = ‘%s,%s’ % (prepend_info, imageData)

dataForImgUpload = {

‘image’ : imageData,

‘imageName’ : basenameOfFile,

‘bulkImgLabel’ : bulkImageLabel,

‘token’ : tokenForApi,

‘imageLocPath’ : fileToProcess

}

r_img = requests.post(imageUploadApiUrl, data=dataForImgUpload)

dataFromImgUpload = r_img.json()

print(dataFromImgUpload);

if dataFromImgUpload[‘status’] == 200 :

dataForStatusAndResult = {

‘jobid’ : dataFromImgUpload[‘jobId’],

‘token’ : tokenForApi

}

## This controls the maximum execution time of the program in your local machine.

## Set to 30 mins

maxAllowedTimeForExec = 30;

totalTimeExecuted = 0;

while True :

try :

r_status = requests.post(jobStatusApiUrl, data=dataForStatusAndResult)

dataFromStatus = r_status.json();

print(dataFromStatus);

if dataFromStatus[‘status’] == 200 :

if (dataFromStatus[‘statusJob’] == ‘COMPLETED’ or dataFromStatus[‘statusJob’] == ‘ERROR’ or dataFromStatus[‘statusJob’] == ‘HOLD’ ) :

break;

## Break on max allowed time

if totalTimeExecuted > (30 * 60) :

break;

## Sleep for 90 seconds before sending another request

sleepTime = 90;

totalTimeExecuted = totalTimeExecuted + sleepTime;

print(“Sleeping for “, sleepTime);

time.sleep(sleepTime);

else :

print(dataFromStatus);

break;

except requests.exceptions.ConnectionError :

time.sleep(3);

continue;

if (dataFromStatus[‘statusJob’] == ‘COMPLETED’ or dataFromStatus[‘statusJob’] == ‘ERROR’ or dataFromStatus[‘statusJob’] == ‘HOLD’) :

r_result = requests.post(jobResultApiUrl, data=dataForStatusAndResult)

dataFromResult = r_result.json();

print(dataFromResult);

else :

print(“Image Upload Status : “, dataFromImgUpload[‘status’], dataFromImgUpload[‘message’]);

except Exception as ex :

print(ex);