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import * as request from "request-promise";
import { Doc, Field } from "../../new_fields/Doc";
import { Cast } from "../../new_fields/Types";
import { Docs } from "../documents/Documents";
import { Utils } from "../../Utils";
import { InkData } from "../../new_fields/InkField";
import { UndoManager } from "../util/UndoManager";
type APIManager<D> = { converter: BodyConverter<D>, requester: RequestExecutor };
type RequestExecutor = (apiKey: string, body: string, service: Service) => Promise<string>;
type AnalysisApplier<D> = (target: Doc, relevantKeys: string[], data: D, ...args: any) => any;
type BodyConverter<D> = (data: D) => string;
type Converter = (results: any) => Field;
export type Tag = { name: string, confidence: number };
export type Rectangle = { top: number, left: number, width: number, height: number };
export enum Service {
ComputerVision = "vision",
Face = "face",
Handwriting = "handwriting"
}
export enum Confidence {
Yikes = 0.0,
Unlikely = 0.2,
Poor = 0.4,
Fair = 0.6,
Good = 0.8,
Excellent = 0.95
}
/**
* A file that handles all interactions with Microsoft Azure's Cognitive
* Services APIs. These machine learning endpoints allow basic data analytics for
* various media types.
*/
export namespace CognitiveServices {
const ExecuteQuery = async <D>(service: Service, manager: APIManager<D>, data: D): Promise<any> => {
const apiKey = await Utils.getApiKey(service);
if (!apiKey) {
console.log(`No API key found for ${service}: ensure index.ts has access to a .env file in your root directory.`);
return undefined;
}
let results: any;
try {
results = await manager.requester(apiKey, manager.converter(data), service).then(json => JSON.parse(json));
} catch {
results = undefined;
}
return results;
};
export namespace Image {
export const Manager: APIManager<string> = {
converter: (imageUrl: string) => JSON.stringify({ url: imageUrl }),
requester: async (apiKey: string, body: string, service: Service) => {
let uriBase;
let parameters;
switch (service) {
case Service.Face:
uriBase = 'face/v1.0/detect';
parameters = {
'returnFaceId': 'true',
'returnFaceLandmarks': 'false',
'returnFaceAttributes': 'age,gender,headPose,smile,facialHair,glasses,' +
'emotion,hair,makeup,occlusion,accessories,blur,exposure,noise'
};
break;
case Service.ComputerVision:
uriBase = 'vision/v2.0/analyze';
parameters = {
'visualFeatures': 'Categories,Description,Color,Objects,Tags,Adult',
'details': 'Celebrities,Landmarks',
'language': 'en',
};
break;
}
const options = {
uri: 'https://eastus.api.cognitive.microsoft.com/' + uriBase,
qs: parameters,
body: body,
headers: {
'Content-Type': 'application/json',
'Ocp-Apim-Subscription-Key': apiKey
}
};
return request.post(options);
},
};
export namespace Appliers {
export const ProcessImage: AnalysisApplier<string> = async (target: Doc, keys: string[], url: string, service: Service, converter: Converter) => {
const batch = UndoManager.StartBatch("Image Analysis");
const storageKey = keys[0];
if (!url || await Cast(target[storageKey], Doc)) {
return;
}
let toStore: any;
const results = await ExecuteQuery(service, Manager, url);
if (!results) {
toStore = "Cognitive Services could not process the given image URL.";
} else {
if (!results.length) {
toStore = converter(results);
} else {
toStore = results.length > 0 ? converter(results) : "Empty list returned.";
}
}
target[storageKey] = toStore;
batch.end();
};
}
export type Face = { faceAttributes: any, faceId: string, faceRectangle: Rectangle };
}
export namespace Inking {
export const Manager: APIManager<InkData[]> = {
converter: (inkData: InkData[]): string => {
let id = 0;
const strokes: AzureStrokeData[] = inkData.map(points => ({
id: id++,
points: points.map(({ X: x, Y: y }) => `${x},${y}`).join(","),
language: "en-US"
}));
return JSON.stringify({
version: 1,
language: "en-US",
unit: "mm",
strokes
});
},
requester: async (apiKey: string, body: string) => {
const xhttp = new XMLHttpRequest();
const serverAddress = "https://api.cognitive.microsoft.com";
const endpoint = serverAddress + "/inkrecognizer/v1.0-preview/recognize";
return new Promise<string>((resolve, reject) => {
xhttp.onreadystatechange = function () {
if (this.readyState === 4) {
const result = xhttp.responseText;
switch (this.status) {
case 200:
return resolve(result);
case 400:
default:
return reject(result);
}
}
};
xhttp.open("PUT", endpoint, true);
xhttp.setRequestHeader('Ocp-Apim-Subscription-Key', apiKey);
xhttp.setRequestHeader('Content-Type', 'application/json');
xhttp.send(body);
});
},
};
export namespace Appliers {
export const ConcatenateHandwriting: AnalysisApplier<InkData[]> = async (target: Doc, keys: string[], inkData: InkData[]) => {
const batch = UndoManager.StartBatch("Ink Analysis");
let results = await ExecuteQuery(Service.Handwriting, Manager, inkData);
if (results) {
results.recognitionUnits && (results = results.recognitionUnits);
target[keys[0]] = Docs.Get.DocumentHierarchyFromJson(results, "Ink Analysis");
const recognizedText = results.map((item: any) => item.recognizedText);
const recognizedObjects = results.map((item: any) => item.recognizedObject);
const individualWords = recognizedText.filter((text: string) => text && text.split(" ").length === 1);
target[keys[1]] = individualWords.length ? individualWords.join(" ") : recognizedObjects.join(", ");
}
batch.end();
};
}
export interface AzureStrokeData {
id: number;
points: string;
language?: string;
}
export interface HandwritingUnit {
version: number;
language: string;
unit: string;
strokes: AzureStrokeData[];
}
}
}
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