Merge pull request #22 from robertknight/node-demos

Add Node examples

README.md

@@ -90,7 +90,8 @@ runOCR();
 
 ## Examples
 
-See the `examples/` directory for projects that show usage of the library.
+See the `examples/` directory for projects that show usage of the library in
+the browser and Node.
 
 ## Documentation
 

examples/node-cli/README.md

@@ -0,0 +1,13 @@
+# tesseract-wasm Node CLI demo
+
+This demo uses the low-level `OCREngine` API to synchronously perform OCR in
+a command-line script.
+
+## Usage
+
+To set up the project and run OCR on `some-image.jpg`, run:
+
+```sh
+npm install
+node ocr.js some-image.jpg
+```

examples/node-cli/ocr.js

@@ -0,0 +1,62 @@
+import { existsSync, readFileSync, writeFileSync } from "node:fs";
+import { fileURLToPath } from "node:url";
+
+import { Command } from "commander";
+import fetch from "node-fetch";
+import { createOCREngine } from "tesseract-wasm";
+import { loadWasmBinary } from "tesseract-wasm/node";
+import sharp from "sharp";
+
+async function loadImage(path) {
+  const image = await sharp(path).ensureAlpha();
+  const { width, height } = await image.metadata();
+  return {
+    data: await image.raw().toBuffer(),
+    width,
+    height,
+  };
+}
+
+/** Resolve a URL relative to the current module. */
+function resolve(path) {
+  return fileURLToPath(new URL(path, import.meta.url).href);
+}
+
+const program = new Command();
+program.description("Extract text from an image");
+program.argument("file");
+program.parse();
+
+// Initialize the OCR engine. In this demo we use the synchronous OCREngine
+// API directly. In a server you would want to use the async OCRClient API
+// instead.
+const wasmBinary = await loadWasmBinary();
+const engine = await createOCREngine({ wasmBinary });
+
+// Fetch the text recognition model and cache it locally, then load it into
+// the OCR engine.
+const modelPath = "eng.traineddata";
+if (!existsSync(modelPath)) {
+  process.stderr.write("Downloading text recognition model...\n");
+  const modelURL =
+    "https://github.com/tesseract-ocr/tessdata_fast/raw/main/eng.traineddata";
+  const response = await fetch(modelURL);
+  if (!response.ok) {
+    process.stderr.write(`Failed to download model from ${modelURL}`);
+    process.exit(1);
+  }
+  const data = await response.arrayBuffer();
+  writeFileSync(modelPath, new Uint8Array(data));
+}
+const model = readFileSync("eng.traineddata");
+engine.loadModel(model);
+
+// Load the image and perform OCR synchronously.
+const image = await loadImage(program.args[0]);
+engine.loadImage(image);
+
+const text = engine.getText((progress) => {
+  process.stderr.write(`\rRecognizing text (${progress}% done)...`);
+});
+process.stderr.write("\n\n");
+process.stdout.write(text);