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index.js
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index.js
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import { createReadStream } from "fs";
import fetch from "node-fetch-3";
import FormData from "form-data";
export class OpticalCharacterRecognition {
constructor(apiKey, modelId) {
if (!apiKey || !modelId)
throw new Error(
"NanoNets SDK Optical Character Recognition Constructor Error: Insufficient parameters passed."
);
else if (typeof apiKey !== "string" || typeof modelId !== "string")
throw new Error(
`NanoNets SDK Optical Character Recognition Constructor Error: Incorrect parameter data type. Expected 'string', got '${typeof apiKey}' and '${typeof modelId}'.`
);
else if (apiKey === "" || modelId === "")
throw new Error(
"NanoNets SDK Optical Character Recognition Constructor Error: Invalid API Key or Model ID. Empty string(s) passed."
);
this.apiKey = apiKey;
this.modelId = modelId;
this.authHeaderVal =
"Basic " + Buffer.from(`${this.apiKey}:`).toString("base64");
}
async getModelDetails() {
const response = await fetch(
`https://app.nanonets.com/api/v2/OCR/Model/${this.modelId}`,
{
headers: {
"Authorization": this.authHeaderVal,
"Accept": "application/json"
}
}
);
const data = response.json();
return data;
}
async getAllPredictedFileData(startInterval, endInterval) {
if (!startInterval || !endInterval)
throw new Error(
"NanoNets SDK Optical Character Recognition getAllPredictedFileData() Error: Insufficient parameters passed."
);
else if (
typeof startInterval !== "number" ||
typeof endInterval !== "number"
)
throw new Error(
`NanoNets SDK Optical Character Recognition getAllPredictedFileData() Error: Incorrect parameter data type. Expected 'number', got '${typeof startInterval}' and '${typeof endInterval}'.`
);
else if (startInterval < 0 || endInterval < 0)
throw new Error(
"NanoNets SDK Optical Character Recognition getAllPredictedFileData() Error: Interval value(s) < 0. Interval values should be non-negative."
);
const response = await fetch(
`https://app.nanonets.com/api/v2/Inferences/Model/${this.modelId}/ImageLevelInferences/?start_day_interval=${startInterval}¤t_batch_day=${endInterval}`,
{
headers: {
"Authorization": this.authHeaderVal,
"Accept": "application/json"
}
}
);
const data = response.json();
return data;
}
async getPredictedFileData(fileId) {
if (!fileId)
throw new Error(
"NanoNets SDK Optical Character Recognition getPredictedFileDataById() Error: File ID parameter not passed."
);
else if (typeof fileId !== "string")
throw new Error(
`NanoNets SDK Optical Character Recognition getPredictedFileDataById() Error: Incorrect parameter data type. Expected 'string', got '${typeof fileId}'.`
);
else if (fileId === "")
throw new Error(
`NanoNets SDK Optical Character Recognition predictUsingFile() Error: Empty file ID passed.`
);
const response = await fetch(
`https://app.nanonets.com/api/v2/Inferences/Model/${this.modelId}/ImageLevelInferences/${fileId}`,
{
headers: {
"Authorization": this.authHeaderVal,
"Accept": "application/json"
}
}
);
const data = response.json();
return data;
}
async predictUsingUrls(urlArray, isAsync = false) {
if (!urlArray)
throw new Error(
"NanoNets SDK Optical Character Recognition predictUsingUrls() Error: URL array parameter not passed."
);
else if (!Array.isArray(urlArray) || typeof isAsync !== "boolean") {
const urlArrayType = Array.isArray(urlArray)
? "array"
: typeof urlArray;
throw new Error(
`NanoNets SDK Optical Character Recognition predictUsingUrls() Error: Incorrect parameter types. Expected 'array' and 'boolean', got '${urlArrayType}' and '${typeof isAsync}'.`
);
} else if (urlArray.length === 0)
throw new Error(
"NanoNets SDK Optical Character Recognition predictUsingUrls() Error: Empty URL array passed."
);
let encodedUrls = new URLSearchParams();
for (let i = 0; i < urlArray.length; i++)
encodedUrls.append("urls", urlArray[i]);
let asyncParam = "";
if (isAsync === true)
asyncParam = "/?" + new URLSearchParams({ "async": "true" });
const response = await fetch(
`https://app.nanonets.com/api/v2/OCR/Model/${this.modelId}/LabelUrls${asyncParam}`,
{
method: "POST",
headers: {
"Authorization": this.authHeaderVal,
"Content-Type": "application/x-www-form-urlencoded",
"Accept": "application/json"
},
body: encodedUrls
}
);
const data = response.json();
return data;
}
async predictUsingFile(filePath, isAsync = false) {
if (!filePath)
throw new Error(
"NanoNets SDK Optical Character Recognition predictUsingFile() Error: File path parameter not passed."
);
else if (typeof filePath !== "string" || typeof isAsync !== "boolean")
throw new Error(
`NanoNets SDK Optical Character Recognition predictUsingFile() Error: Incorrect parameter data types. Expected 'string' and 'boolean', got '${typeof filePath}' and '${typeof isAsync}'.`
);
else if (filePath === "")
throw new Error(
`NanoNets SDK Optical Character Recognition predictUsingFile() Error: Empty file path passed.`
);
const fileStream = createReadStream(filePath);
const formData = new FormData();
formData.append("file", fileStream);
let asyncParam = "";
if (isAsync === true)
asyncParam = "/?" + new URLSearchParams({ "async": "true" });
const response = await fetch(
`https://app.nanonets.com/api/v2/OCR/Model/${this.modelId}/LabelFile${asyncParam}`,
{
method: "POST",
headers: {
"Authorization": this.authHeaderVal,
"Accept": "application/json"
},
body: formData
}
);
const data = response.json();
return data;
}
}
export class ImageClassification {
constructor(apiKey, modelId) {
if (!apiKey || !modelId)
throw new Error(
"NanoNets SDK Image Classification Constructor Error: Insufficient parameters passed."
);
else if (typeof apiKey !== "string" || typeof modelId !== "string")
throw new Error(
`NanoNets SDK Image Classification Constructor Error: Incorrect parameter data type. Expected 'string', got '${typeof apiKey}' and '${typeof modelId}'.`
);
else if (apiKey === "" || modelId === "")
throw new Error(
"NanoNets SDK Image Classification Constructor Error: Invalid API Key or Model ID. Empty string(s) passed."
);
this.apiKey = apiKey;
this.modelId = modelId;
this.authHeaderVal =
"Basic " + Buffer.from(`${this.apiKey}:`).toString("base64");
}
async getModelDetails() {
const response = await fetch(
`https://app.nanonets.com/api/v2/ImageCategorization/Model/?modelId=${this.modelId}`,
{
headers: {
"Authorization": this.authHeaderVal,
"Accept": "application/json"
}
}
);
const data = response.json();
return data;
}
async predictUsingUrls(urlArray) {
if (!urlArray)
throw new Error(
"NanoNets SDK Image Classification predictUsingUrls() Error: URL array parameter not passed."
);
else if (!Array.isArray(urlArray))
throw new Error(
`NanoNets SDK Image Classification predictUsingUrls() Error: Incorrect parameter type. Expected 'array', got '${typeof urlArray}'.`
);
else if (urlArray.length === 0)
throw new Error(
"NanoNets SDK Image Classification predictUsingUrls() Error: Empty URL array passed."
);
let encodedData = new URLSearchParams();
for (let i = 0; i < urlArray.length; i++) {
encodedData.append("urls", urlArray[i]);
}
encodedData.append("modelId", this.modelId);
const response = await fetch(
`https://app.nanonets.com/api/v2/ImageCategorization/LabelUrls`,
{
method: "POST",
headers: {
"Authorization": this.authHeaderVal,
"Content-Type": "application/x-www-form-urlencoded",
"Accept": "application/json"
},
body: encodedData
}
);
const data = response.json();
return data;
}
async predictUsingFile(filePath) {
if (!filePath)
throw new Error(
"NanoNets SDK Image Classification predictUsingFile() Error: File path parameter not passed."
);
else if (typeof filePath !== "string")
throw new Error(
`NanoNets SDK Image Classification predictUsingFile() Error: Incorrect parameter data type. Expected 'string', got '${typeof filePath}'.`
);
else if (filePath === "")
throw new Error(
`NanoNets SDK Image Classification predictUsingFile() Error: Empty file path passed.`
);
const fileStream = createReadStream(filePath);
const formData = new FormData();
formData.append("file", fileStream);
formData.append("modelId", this.modelId);
const response = await fetch(
`https://app.nanonets.com/api/v2/ImageCategorization/LabelFile`,
{
method: "POST",
headers: {
"Authorization": this.authHeaderVal,
"Accept": "application/json"
},
body: formData
}
);
const data = response.json();
return data;
}
}