Fix reality capture sdks examples and readme files.

.gitignore

@@ -4,4 +4,5 @@ lib/
 coverage/
 .env
 .idea/
-
+*.configStore/
+dist/

CONTRIBUTING.md

@@ -47,9 +47,9 @@ Every change must be tested with proper unit tests.
 
 ### Build Instructions
 
-See sub Readme files in typescript/packages, typescript/examples or python/ for more  information about build instructions.
+See Readme file for more information about build instructions.
 
-> Note: It is a good idea to `npm install` after each `git pull` as dependencies may have changed.
+> Note: It is a good idea to `pnpm install` after each `git pull` as dependencies may have changed.
 ### Making and Testing Changes
 
 1. Make source code changes on a new Git branch

LICENSE.md

@@ -1,6 +1,6 @@
 # MIT License
 
-Copyright © 2023 Bentley Systems, Incorporated. All rights reserved.
+Copyright © 2024 Bentley Systems, Incorporated. All rights reserved.
 
 Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
 

README.md

@@ -15,7 +15,7 @@ Besides, a typescript web application example is available to show how to create
 
 Reality data utils to upload and download results
 
-- [Reality Data utils](./typescript/packages/reality-data-transfer/README.md)
+- [Reality Data transfer utils](./typescript/packages/reality-data-transfer/README.md)
 
 All the packages are available in python, except Reality Management
 
@@ -31,5 +31,5 @@ All the packages are available in python, except Reality Management
 
 1. Clone repository (first time) with `git clone` or pull updates to the repository (subsequent times) with `git pull`
 2. Install dependencies: `pnpm update` or `pnpm install`
-3. Build source: `pnpm build`
-4. Run unit tests : create a .env file based on template.env, then : `pnpm coverage`
+3. Build source: `npm run build`
+4. Run unit tests : create a .env file based on template.env, then : `npm run coverage`

typescript/examples/code-samples/README.md

@@ -30,7 +30,7 @@ To build and run the source code locally you will need a few things:
 - Build the project
 
   ```sh
-  pnpm run build
+  npm run build
   ```
 
 - Create a new `.env` file, based on `template.env`. Fill in the required fields in the `.env` configuration file.
@@ -40,9 +40,16 @@ To build and run the source code locally you will need a few things:
 
 - Run reality data creation example
 
+- Run context capture example
+
+  ```sh
+  cd examples/code-samples
+  npm run start-cc-example
+  ```
+
   ```sh
   cd examples/code-samples
-  npm run start-rd-example
+  npm run start-data-example
   ```
 
 - Run 2d objects detection example
@@ -52,16 +59,16 @@ To build and run the source code locally you will need a few things:
   npm run start-o2d-example
   ```
 
-- Run 3d lines detection example
+- Run reality conversion example
 
   ```sh
   cd examples/code-samples
-  npm run start-l3d-example
+  npm run start-rcs-example
   ```
 
-- Run context capture example
+- Run 2d segmentation example
 
   ```sh
   cd examples/code-samples
-  npm run start-cc-example
-  ```
+  npm run start-s2d-example
+  ```

typescript/examples/code-samples/package.json

@@ -8,11 +8,11 @@
     "clean": "rimraf lib build .rush",
     "lint": "eslint ./src --ext .ts,.tsx ",
     "lint-fix": "eslint ./src --fix --ext .ts,.tsx",
-    "start-cc-example": "node ./lib/ContextCapture.js",
-    "start-l3d-example": "node ./lib/Lines3D.js",
-    "start-o2d-example": "node ./lib/Objects2D.js",
+    "start-modeling-example": "node ./lib/Modeling.js",
     "start-data-example": "node ./lib/DataTransfer.js",
+    "start-o2d-example": "node ./lib/Objects2D.js",
     "start-rcs-example": "node ./lib/RealityConversion.js",
+    "start-s2d-example": "node ./lib/Segmentation2D.js",
     "coverage": "",
     "integration-tests": ""
   },

typescript/examples/code-samples/src/DataTransfer.ts

@@ -8,15 +8,17 @@ import { RealityDataTransferNode, defaultProgressHook } from "@itwin/reality-dat
 import { RealityDataType } from "@itwin/reality-capture-common";
 import { NodeCliAuthorizationClient } from "@itwin/node-cli-authorization";
 
-
 async function runRealityDataExample() {
-    const imageCollection = "path to the folder yu want to upload";
+    /**
+     * This example uploads an images folder in the cloud, and downloads it
+     */
+    const images = "path to the images you want to upload";
     const outputPath = "path to the folder where you want to save downloads";
-    const imageCollectionName = "Test Moto Photos";
+    const imagesName = "Test Upload Moto Photos";
 
     dotenv.config();
 
-    const projectId = process.env.IMJS_PROJECT_ID ?? "";
+    const iTwinId = process.env.IMJS_PROJECT_ID ?? "";
     const clientId = process.env.IMJS_CLIENT_ID ?? "";
     const redirectUrl = process.env.IMJS_REDIRECT_URL ?? "";
     const env = process.env.IMJS_ENV ?? "";
@@ -41,16 +43,15 @@ async function runRealityDataExample() {
     realityDataService.setDownloadHook(defaultProgressHook);
     console.log("Service initialized");
 
-    // Upload CCImageCollection
-    console.log("Uploading CCImagesCollection to cloud");
-    const id = await realityDataService.uploadRealityData(imageCollection, imageCollectionName, 
-        RealityDataType.CC_IMAGE_COLLECTION, projectId);
-    console.log("CCImagesCollection uploaded successfully");
+    // Upload images
+    console.log("Uploading images to cloud");
+    const id = await realityDataService.uploadRealityData(images, imagesName, RealityDataType.CC_IMAGE_COLLECTION, iTwinId);
+    console.log("Images uploaded successfully");
 
-    // Download CCImageCollection
-    console.log("Downloading CCImagesCollection");
-    await realityDataService.downloadRealityData(id, outputPath, projectId);
-    console.log("CCImagesCollection downloaded successfully");
+    // Download images
+    console.log("Downloading images");
+    await realityDataService.downloadRealityData(id, outputPath, iTwinId);
+    console.log("Images downloaded successfully");
 }
 
 runRealityDataExample();

typescript/examples/code-samples/src/ContextCapture.ts → typescript/examples/code-samples/src/Modeling.ts

@@ -13,19 +13,22 @@ import { NodeCliAuthorizationClient } from "@itwin/node-cli-authorization";
 
 export async function sleep(ms: number) { return new Promise(resolve => setTimeout(resolve, ms)); }
 
-async function main() {
-    const ccImageCollection = "path to your image folder";
+async function runModelingExample() {
+    /**
+     * This example submits a Full Modeling job (Calibration + Reconstruction), and will download the reconstruction output as a 3mx file.
+     */
+    const images = "path to your image folder";
     const ccOrientations = "path to the folder where your ccorientation file is";
     const outputPath = "path to the folder where you want to save outputs";
 
     dotenv.config();
 
     const jobName = "Reality Modeling job SDK sample";
     const workspaceName = "Reality Modeling test workspace";
-    const ccImageCollectionName = "Reality Modeling test photos";
+    const imagesName = "Reality Modeling test photos";
     const ccOrientationsName = "Reality Modeling test ccorientations";
 
-    const projectId = process.env.IMJS_PROJECT_ID ?? "";
+    const iTwindId = process.env.IMJS_PROJECT_ID ?? "";
     const clientId = process.env.IMJS_CLIENT_ID ?? "";
     const redirectUrl = process.env.IMJS_REDIRECT_URL ?? "";
     const env = process.env.IMJS_ENV ?? "";
@@ -60,40 +63,39 @@ async function main() {
     console.log("Service initialized");
 
     try {
-        // Creating reference table and uploading ccimageCollection, ccOrientations if necessary (not yet on the cloud)
+        // Creating reference table and uploading images, ccOrientations if necessary (not yet on the cloud)
         const references = new ReferenceTableNode();
         const referencesPath = path.join(outputPath, "test_references_typescript.txt");
         if(fs.existsSync(referencesPath) && fs.lstatSync(referencesPath).isFile()) {
             console.log("Loading preexistent references");
             await references.load(referencesPath);
         }
 
-        // Upload CCImageCollection
-        if(!references.hasLocalPath(ccImageCollection)) {
-            console.log("No reference to CCimage Collections found, uploading local files to cloud");
-            const id = await realityDataService.uploadRealityData(ccImageCollection, ccImageCollectionName, 
-                RealityDataType.CC_IMAGE_COLLECTION, projectId);
-            references.addReference(ccImageCollection, id);
+        // Upload images
+        if(!references.hasLocalPath(images)) {
+            console.log("No reference to images found, uploading local files to cloud");
+            const id = await realityDataService.uploadRealityData(images, imagesName, 
+                RealityDataType.CC_IMAGE_COLLECTION, iTwindId);
+            references.addReference(images, id);
         }
 
-        // Upload Oriented photos (ccOrientations)
+        // Upload ccOrientations
         if(!references.hasLocalPath(ccOrientations)) {
             console.log("No reference to cc orientations found, uploading local files to cloud");
-            const id = await realityDataService.uploadCCOrientations(ccOrientations, ccOrientationsName, projectId, references);
+            const id = await realityDataService.uploadCCOrientations(ccOrientations, ccOrientationsName, iTwindId, references);
             references.addReference(ccOrientations, id);
         }
 
         await references.save(referencesPath);
         console.log("Checked data upload");
 
         // Create workspace
-        const workspaceId = await contextCaptureService.createWorkspace(workspaceName, projectId);
+        const workspaceId = await contextCaptureService.createWorkspace(workspaceName, iTwindId);
 
         const settings = new CCJobSettings();
-        settings.inputs = [references.getCloudIdFromLocalPath(ccImageCollection), references.getCloudIdFromLocalPath(ccOrientations)];
+        settings.inputs = [references.getCloudIdFromLocalPath(images), references.getCloudIdFromLocalPath(ccOrientations)];
         settings.outputs.threeMX = "threeMX";
-        settings.meshQuality = CCJobQuality.MEDIUM;
-
+        settings.meshQuality = CCJobQuality.DRAFT;
         console.log("Settings created");
 
         const jobId = await contextCaptureService.createJob(CCJobType.FULL, settings, jobName, workspaceId);
@@ -129,12 +131,12 @@ async function main() {
         const properties = await contextCaptureService.getJobProperties(jobId);
         console.log("Downloading outputs");
         const threeMXId = (properties.settings as CCJobSettings).outputs.threeMX;
-        realityDataService.downloadRealityData(threeMXId, outputPath, projectId);
+        realityDataService.downloadRealityData(threeMXId, outputPath, iTwindId);
         console.log("Successfully downloaded output");
     }
     catch(error: any) {
         console.log(error);
     }
 }
 
-main();
+runModelingExample();

typescript/examples/code-samples/src/Objects2D.ts

@@ -9,16 +9,19 @@ import * as fs from "fs";
 import * as dotenv from "dotenv";
 import { JobState, RealityDataType } from "@itwin/reality-capture-common";
 import { NodeCliAuthorizationClient } from "@itwin/node-cli-authorization";
-import { RealityDataTransferNode, ReferenceTableNode } from "@itwin/reality-data-transfer";
+import { RealityDataTransferNode, ReferenceTableNode, defaultProgressHook } from "@itwin/reality-data-transfer";
 
 
 export async function sleep(ms: number) { return new Promise(resolve => setTimeout(resolve, ms)); }
 
 async function runObjects2DExample() {
-    const imageCollection = "path to your image collection";
-    const photoContextScene = "path to the folder where your context scene file is";
+    /**
+     * This example submits an objects2d analysis job, and downloads an annotations context scene
+     */
+    const imageCollection = "path to your images";
+    const photoContextScene = "path to the folder where your context scene file is referenced";
     const photoObjectDetector = "path to the folder where your detector is";
-    const outputPath = "path to the folder where you want to save outputs";
+    const outputPath = "path to the folder where you want to save the annotatations context scene";
 
     dotenv.config();
 
@@ -27,7 +30,7 @@ async function runObjects2DExample() {
     const contextSceneName = "Test Moto Scene";
     const detectorName = "Test O2D Photo Detector";
 
-    const projectId = process.env.IMJS_PROJECT_ID ?? "";
+    const iTwinId = process.env.IMJS_PROJECT_ID ?? "";
     const clientId = process.env.IMJS_CLIENT_ID ?? "";
     const redirectUrl = process.env.IMJS_REDIRECT_URL ?? "";
     const env = process.env.IMJS_ENV ?? "";
@@ -48,6 +51,9 @@ async function runObjects2DExample() {
     else
         realityDataService = new RealityDataTransferNode(authorizationClient.getAccessToken.bind(authorizationClient), "qa-");
 
+    realityDataService.setUploadHook(defaultProgressHook);
+    realityDataService.setDownloadHook(defaultProgressHook);
+
     let realityDataAnalysisService;
     if(env === "prod")
         realityDataAnalysisService = new RealityDataAnalysisService(authorizationClient.getAccessToken.bind(authorizationClient));
@@ -57,34 +63,34 @@ async function runObjects2DExample() {
         realityDataAnalysisService = new RealityDataAnalysisService(authorizationClient.getAccessToken.bind(authorizationClient), "dev-");
     console.log("Service initialized");
 
-    // Creating reference table and uploading ccimageCollection, contextScene and detector if necessary (not yet on the cloud)
+    // Creating reference table and uploading images, contextScene and detector if necessary (not yet on the cloud)
     const references = new ReferenceTableNode();
     const referencesPath = path.join(outputPath, "test_references_typescript.txt");
     if(fs.existsSync(referencesPath) && fs.lstatSync(referencesPath).isFile()) {
         console.log("Loading preexistent references");
         await references.load(referencesPath);
     }
 
-    // Upload CCImageCollection
+    // Upload images
     if(!references.hasLocalPath(imageCollection)) {
-        console.log("No reference to CCimage Collections found, uploading local files to cloud");
+        console.log("No reference to images found, uploading local files to cloud");
         const id = await realityDataService.uploadRealityData(imageCollection, imageCollectionName, 
-            RealityDataType.CC_IMAGE_COLLECTION, projectId);
+            RealityDataType.CC_IMAGE_COLLECTION, iTwinId);
         references.addReference(imageCollection, id);
     }
 
     // Upload ContextScene
     if(!references.hasLocalPath(photoContextScene)) {
         console.log("No reference to ContextScene found, uploading local files to cloud");
-        const id = await realityDataService.uploadContextScene(photoContextScene, contextSceneName, projectId, references);
+        const id = await realityDataService.uploadContextScene(photoContextScene, contextSceneName, iTwinId, references);
         references.addReference(photoContextScene, id);
     }
 
     // Upload Detector
     if(!references.hasLocalPath(photoObjectDetector)) {
         console.log("No reference to detector found, uploading local files to cloud");
         const id = await realityDataService.uploadRealityData(photoObjectDetector, detectorName, RealityDataType.CONTEXT_DETECTOR, 
-            projectId);
+            iTwinId);
         references.addReference(photoObjectDetector, id);
     }
 
@@ -97,7 +103,7 @@ async function runObjects2DExample() {
     settings.outputs.objects2D = "objects2D";
     console.log("Settings created");
 
-    const jobId = await realityDataAnalysisService.createJob(settings, jobName, projectId);
+    const jobId = await realityDataAnalysisService.createJob(settings, jobName, iTwinId);
     console.log("Job created");
 
     await realityDataAnalysisService.submitJob(jobId);
@@ -130,7 +136,7 @@ async function runObjects2DExample() {
     const properties = await realityDataAnalysisService.getJobProperties(jobId);
     console.log("Downloading outputs");
     const objects2DId = (properties.settings as O2DJobSettings).outputs.objects2D;
-    realityDataService.downloadContextScene(objects2DId, outputPath, projectId, references);
+    realityDataService.downloadContextScene(objects2DId, outputPath, iTwinId, references);
     console.log("Successfully downloaded output");
 }