Move InferenceImage to smart-tools (#528)

Author: jpggvilaca

web_ui/packages/smart-tools/index.ts

@@ -6,4 +6,6 @@ export { default as OpenCVLoader } from './src/utils/opencv-loader';
 export { Watershed } from './src/watershed/watershed';
 export { type WatershedInstance, type WatershedPolygon } from './src/watershed/interfaces';
 
+export { InferenceImage } from './src/inference-image/inference-image';
+
 export { formatContourToPoints, approximateShape } from './src/utils/utils';

web_ui/packages/smart-tools/src/inference-image/inference-image.ts

@@ -0,0 +1,38 @@
+// Copyright (C) 2022-2025 Intel Corporation
+// LIMITED EDGE SOFTWARE DISTRIBUTION LICENSE
+
+import type OpenCVTypes from 'OpenCVTypes';
+
+import { formatImageData } from '../utils/utils';
+
+export class InferenceImage {
+    constructor(private CV: OpenCVTypes.cv) {}
+
+    resize(imageData: ImageData, width: number, height: number): ImageData {
+        const img = this.getImage(imageData);
+
+        const size = new this.CV.Size(width, height);
+        const dst: OpenCVTypes.Mat = new this.CV.Mat();
+        const colorMap: OpenCVTypes.Mat = new this.CV.Mat();
+
+        this.CV.resize(img, dst, size, 0, 0, this.CV.INTER_CUBIC);
+        this.CV.applyColorMap(dst, colorMap, this.CV.COLORMAP_JET);
+        this.CV.cvtColor(colorMap, colorMap, this.CV.COLOR_BGR2RGB);
+
+        const finalImageData = formatImageData(this.CV, colorMap);
+
+        img.delete();
+        dst.delete();
+        colorMap.delete();
+
+        return finalImageData;
+    }
+
+    getImage(imageData: ImageData): OpenCVTypes.Mat {
+        const data = this.CV.matFromImageData(imageData);
+
+        this.CV.cvtColor(data, data, this.CV.COLOR_RGBA2RGB, 0);
+
+        return data;
+    }
+}

web_ui/packages/smart-tools/src/utils/utils.ts

@@ -36,3 +36,27 @@ export const approximateShape = (CV: OpenCVTypes.cv, contour: OpenCVTypes.Mat, i
 
     return newContour;
 };
+
+export const formatImageData = (CV: OpenCVTypes.cv, mat: OpenCVTypes.Mat): ImageData => {
+    const img = new CV.Mat();
+    const depth = mat.type() % 8;
+    const scale = depth <= CV.CV_8S ? 1 : depth <= CV.CV_32S ? 1 / 256 : 255;
+    const shift = depth === CV.CV_8S || depth === CV.CV_16S ? 128 : 0;
+
+    mat.convertTo(img, CV.CV_8U, scale, shift);
+
+    switch (img.type()) {
+        case CV.CV_8UC1:
+            CV.cvtColor(img, img, CV.COLOR_GRAY2RGBA);
+            break;
+        case CV.CV_8UC3:
+            CV.cvtColor(img, img, CV.COLOR_RGB2RGBA);
+            break;
+        case CV.CV_8UC4:
+            break;
+        default:
+            throw new Error('Bad number of channels (Source image must have 1, 3 or 4 channels)');
+    }
+
+    return new ImageData(new Uint8ClampedArray(img.data), img.cols, img.rows);
+};

web_ui/src/webworkers/inference-image.worker.ts

@@ -1,64 +1,26 @@
 // Copyright (C) 2022-2025 Intel Corporation
 // LIMITED EDGE SOFTWARE DISTRIBUTION LICENSE
 
-//  Dependencies get bundled into the worker
-
-import { OpenCVLoader } from '@geti/smart-tools';
+import { InferenceImage, OpenCVLoader } from '@geti/smart-tools';
 import { expose } from 'comlink';
 import type OpenCVTypes from 'OpenCVTypes';
 
-import { formatImageData } from './utils';
-
 declare const self: DedicatedWorkerGlobalScope;
 
-let CV: OpenCVTypes.cv | null = null;
-
-const terminate = (): void => {
-    self.close();
-};
-
-class InferenceImage {
-    resize(imageData: ImageData, width: number, height: number): ImageData {
-        const img = this.getImage(imageData);
-
-        const size = new CV.Size(width, height);
-        const dst: OpenCVTypes.Mat = new CV.Mat();
-        const colorMap: OpenCVTypes.Mat = new CV.Mat();
-
-        CV.resize(img, dst, size, 0, 0, CV.INTER_CUBIC);
-        CV.applyColorMap(dst, colorMap, CV.COLORMAP_JET);
-        CV.cvtColor(colorMap, colorMap, CV.COLOR_BGR2RGB);
+let opencv: OpenCVTypes;
 
-        const finalImageData = formatImageData(CV, colorMap);
+const waitForOpenCV = async () => {
+    if (opencv) return true;
 
-        img.delete();
-        dst.delete();
-        colorMap.delete();
+    opencv = await OpenCVLoader();
 
-        return finalImageData;
+    if ('ready' in opencv) {
+        await opencv.ready;
     }
 
-    getImage(imageData: ImageData): OpenCVTypes.Mat {
-        const data = CV.matFromImageData(imageData);
-
-        CV.cvtColor(data, data, CV.COLOR_RGBA2RGB, 0);
-
-        return data;
-    }
-}
-
-const waitForOpenCV = async (): Promise<boolean> => {
-    if (CV) {
-        return true;
-    } else {
-        return OpenCVLoader().then((cvInstance: OpenCVTypes.cv) => {
-            CV = cvInstance;
-
-            return true;
-        });
-    }
+    return false;
 };
 
-const WorkerApi = { InferenceImage, waitForOpenCV, terminate };
+const WorkerApi = { InferenceImage, waitForOpenCV, terminate: self.close };
 
 expose(WorkerApi);

web_ui/src/webworkers/utils.ts

@@ -44,30 +44,6 @@ export const getPointsFromMat = (mat: OpenCVTypes.Mat, offset = { x: 0, y: 0 }):
     return points;
 };
 
-export const formatImageData = (CV: OpenCVTypes.cv, mat: OpenCVTypes.Mat): ImageData => {
-    const img = new CV.Mat();
-    const depth = mat.type() % 8;
-    const scale = depth <= CV.CV_8S ? 1 : depth <= CV.CV_32S ? 1 / 256 : 255;
-    const shift = depth === CV.CV_8S || depth === CV.CV_16S ? 128 : 0;
-
-    mat.convertTo(img, CV.CV_8U, scale, shift);
-
-    switch (img.type()) {
-        case CV.CV_8UC1:
-            CV.cvtColor(img, img, CV.COLOR_GRAY2RGBA);
-            break;
-        case CV.CV_8UC3:
-            CV.cvtColor(img, img, CV.COLOR_RGB2RGBA);
-            break;
-        case CV.CV_8UC4:
-            break;
-        default:
-            throw new Error('Bad number of channels (Source image must have 1, 3 or 4 channels)');
-    }
-
-    return new ImageData(new Uint8ClampedArray(img.data), img.cols, img.rows);
-};
-
 // For debugging purposes, not being used atm
 // eslint-disable-next-line @typescript-eslint/no-unused-vars
 const logMat = (mat: OpenCVTypes.Mat, name: string): void => {