Adding a example

.dockerignore

@@ -0,0 +1,2 @@
+node_modules
+images/

.gitignore

@@ -5,7 +5,8 @@ npm-debug.log*
 yarn-debug.log*
 yarn-error.log*
 lerna-debug.log*
-
+node_modules
+package-lock.json
 # Diagnostic reports (https://nodejs.org/api/report.html)
 report.[0-9]*.[0-9]*.[0-9]*.[0-9]*.json
 

Dockerfile

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+FROM ubuntu:16.04
+USER root
+COPY . .
+RUN apt-get update
+RUN apt-get -y install curl gnupg git cmake build-essential
+RUN curl -sL https://deb.nodesource.com/setup_11.x  | bash -
+RUN apt-get -y install nodejs
+RUN npm install
+CMD "npm start"

README.md

@@ -1 +1,25 @@
-# object-detection-node
+# object-detection-node
+This is an example on how we can use ***@cloud-annotations*** in Nodejs.
+
+You can find an in depth walkthrough for training a TensorFlow.js model [here](https://github.com/cloud-annotations/training/).
+
+## Setup
+`git clone` the repo and `cd` into it by running the following command:
+
+```bash
+git clone https://github.com/cloud-annotations/object-detection-node.git
+cd object-detection-node
+```
+
+### `npm install`
+
+> **Note: You’ll need to have Node 8.10.0 or later on your local development machine.** You can use [nvm](https://github.com/creationix/nvm#installation) (macOS/Linux) or [nvm-windows](https://github.com/coreybutler/nvm-windows#node-version-manager-nvm-for-windows) to easily switch Node versions between different projects.
+
+## Add TensorFlow.js Model to the App
+Copy the `model_web` directory generated from the object detection walkthrough and paste it into the root directory of this repo.
+
+## Run the App
+### `npm start`
+
+It will open a window and show live stream of processed images through @cloud-annotations/models-node
+![alt text](images/1.png)

index.js

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+var cv = require("opencv4nodejs");
+const models = require('@cloud-annotations/models-node');
+const vCap = new cv.VideoCapture(0);
+const delay = 50;
+let done = false;
+const blue = new cv.Vec(255, 0, 0);
+const thickness = 1;
+async function load() {
+    try {
+        const model = await models.load('model_web');
+        console.log("model is loaded");
+        while (!done) {
+            let frame = vCap.read();
+            var buffer = cv.imencode('.jpg', frame)
+            const results = await model.detect(buffer);
+            console.log(results);
+            results.forEach(element => {
+                frame.drawRectangle(
+                    new cv.Point(element.bbox[0], element.bbox[1]),
+                    new cv.Point(element.bbox[0]+ element.bbox[2], element.bbox[1] + element.bbox[3]),
+                    blue,
+                    cv.LINE_8,
+                    thickness
+                  );
+                  frame.putText(element.label, new cv.Point2(element.bbox[0], element.bbox[1]+element.bbox[3]), cv.FONT_HERSHEY_SIMPLEX, 2, new cv.Vec3(0, 255, 0), 2)
+            });
+            if (frame.empty) {
+                vCap.reset();
+                frame = vCap.read();
+            }
+            cv.waitKey(delay);
+            // cv.imshow("frame", frame)
+        }
+
+    } catch(err) {
+        console.log(err)
+
+    }
+}
+load()

model_web/labels.json

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+["mask", "nomask"]

package.json

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+{
+  "name": "object-detection-node",
+  "version": "1.0.0",
+  "description": "",
+  "main": "index.js",
+  "scripts": {
+    "test": "echo \"Error: no test specified\" && exit 1",
+    "start": "node index.js"
+  },
+  "repository": {
+    "type": "git",
+    "url": "git+https://github.com/SaifRehman/object-detection-node.git"
+  },
+  "dependencies": {
+    "@cloud-annotations/models-node": "0.0.3",
+    "@tensorflow/tfjs": "^1.4.0",
+    "@tensorflow/tfjs-node": "^1.7.4",
+    "opencv4nodejs": "^5.6.0"
+  },
+  "opencv4nodejs": {
+    "autoBuildFlags": "-DOPENCV_GENERATE_PKGCONFIG=ON -DOPENCV_PC_FILE_NAME=opencv.pc",
+    "autoBuildOpencvVersion": "4.1.0"
+  },
+  "author": "",
+  "license": "ISC",
+  "bugs": {
+    "url": "https://github.com/SaifRehman/object-detection-node/issues"
+  },
+  "homepage": "https://github.com/SaifRehman/object-detection-node#readme"
+}