Stylistic

desktop/.eslintrc.js

@@ -5,8 +5,7 @@ module.exports = {
         "eslint:recommended",
         "plugin:@typescript-eslint/eslint-recommended",
         "plugin:@typescript-eslint/strict-type-checked",
-        /* What we really want eventually */
-        // "plugin:@typescript-eslint/stylistic-type-checked",
+        "plugin:@typescript-eslint/stylistic-type-checked",
     ],
     plugins: ["@typescript-eslint"],
     parser: "@typescript-eslint/parser",

desktop/src/main/services/ml-clip.ts

@@ -45,7 +45,7 @@ const clipImageEmbedding_ = async (jpegFilePath: string) => {
             `onnx/clip image embedding took ${Date.now() - t1} ms (prep: ${t2 - t1} ms, inference: ${Date.now() - t2} ms)`,
     );
     /* Need these model specific casts to type the result */
-    const imageEmbedding = ensure(results["output"]).data as Float32Array;
+    const imageEmbedding = ensure(results.output).data as Float32Array;
     return normalizeEmbedding(imageEmbedding);
 };
 
@@ -120,13 +120,12 @@ const getRGBData = async (jpegFilePath: string): Promise<number[]> => {
 
 const normalizeEmbedding = (embedding: Float32Array) => {
     let normalization = 0;
-    for (let index = 0; index < embedding.length; index++) {
-        normalization += ensure(embedding[index]) * ensure(embedding[index]);
-    }
+    for (const v of embedding) normalization += v * v;
+
     const sqrtNormalization = Math.sqrt(normalization);
-    for (let index = 0; index < embedding.length; index++) {
+    for (let index = 0; index < embedding.length; index++)
         embedding[index] = ensure(embedding[index]) / sqrtNormalization;
-    }
+
     return embedding;
 };
 
@@ -168,6 +167,6 @@ export const clipTextEmbeddingIfAvailable = async (text: string) => {
         () =>
             `onnx/clip text embedding took ${Date.now() - t1} ms (prep: ${t2 - t1} ms, inference: ${Date.now() - t2} ms)`,
     );
-    const textEmbedding = ensure(results["output"]).data as Float32Array;
+    const textEmbedding = ensure(results.output).data as Float32Array;
     return normalizeEmbedding(textEmbedding);
 };

desktop/src/main/services/ml-face.ts

@@ -24,7 +24,7 @@ export const detectFaces = async (input: Float32Array) => {
     };
     const results = await session.run(feeds);
     log.debug(() => `onnx/yolo face detection took ${Date.now() - t} ms`);
-    return ensure(results["output"]).data;
+    return ensure(results.output).data;
 };
 
 const cachedFaceEmbeddingSession = makeCachedInferenceSession(
@@ -47,7 +47,6 @@ export const faceEmbedding = async (input: Float32Array) => {
     const results = await session.run(feeds);
     log.debug(() => `onnx/yolo face embedding took ${Date.now() - t} ms`);
     /* Need these model specific casts to extract and type the result */
-    return (results.embeddings as unknown as Record<string, unknown>)[
-        "cpuData"
-    ] as Float32Array;
+    return (results.embeddings as unknown as Record<string, unknown>)
+        .cpuData as Float32Array;
 };

desktop/src/main/services/upload.ts

@@ -14,7 +14,7 @@ export const listZipItems = async (zipPath: string): Promise<ZipItem[]> => {
     for (const entry of Object.values(entries)) {
         const basename = path.basename(entry.name);
         // Ignore "hidden" files (files whose names begins with a dot).
-        if (entry.isFile && basename.length > 0 && basename[0] != ".") {
+        if (entry.isFile && basename.startsWith(".")) {
             // `entry.name` is the path within the zip.
             entryNames.push(entry.name);
         }

desktop/src/main/utils/temp.ts

@@ -98,7 +98,9 @@ export const makeFileForDataOrPathOrZipItem = async (
 ): Promise<FileForDataOrPathOrZipItem> => {
     let path: string;
     let isFileTemporary: boolean;
-    let writeToTemporaryFile = async () => {};
+    let writeToTemporaryFile = async () => {
+        /* no-op */
+    };
 
     if (typeof dataOrPathOrZipItem == "string") {
         path = dataOrPathOrZipItem;