fork from https://github.com/mozilla/pdf.js.git

test/unit/stream_spec.js

@@ -0,0 +1,78 @@
+/* Copyright 2017 Mozilla Foundation
+ *
+ * Licensed under the Apache License, Version 2.0 (the "License");
+ * you may not use this file except in compliance with the License.
+ * You may obtain a copy of the License at
+ *
+ *     http://www.apache.org/licenses/LICENSE-2.0
+ *
+ * Unless required by applicable law or agreed to in writing, software
+ * distributed under the License is distributed on an "AS IS" BASIS,
+ * WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+ * See the License for the specific language governing permissions and
+ * limitations under the License.
+ */
+
+import { createImage } from "../../src/core/editor/pdf_images.js";
+import { Dict } from "../../src/core/primitives.js";
+import { FlateStream } from "../../src/core/flate_stream.js";
+import { isNodeJS } from "../../src/shared/util.js";
+import { PredictorStream } from "../../src/core/predictor_stream.js";
+import { Stream } from "../../src/core/stream.js";
+
+describe("stream", function () {
+  describe("PredictorStream", function () {
+    it("should decode simple predictor data", function () {
+      const dict = new Dict();
+      dict.set("Predictor", 12);
+      dict.set("Colors", 1);
+      dict.set("BitsPerComponent", 8);
+      dict.set("Columns", 2);
+
+      const input = new Stream(
+        new Uint8Array([2, 100, 3, 2, 1, 255, 2, 1, 255]),
+        0,
+        9,
+        dict
+      );
+      const predictor = new PredictorStream(input, /* length = */ 9, dict);
+      const result = predictor.getBytes(6);
+
+      expect(result).toEqual(new Uint8Array([100, 3, 101, 2, 102, 1]));
+    });
+
+    it("should decode the FlateDecode stream produced by createImage", async function () {
+      if (isNodeJS) {
+        pending("OffscreenCanvas is not supported in Node.js.");
+      }
+      const width = 2;
+      const height = 2;
+      const canvas = new OffscreenCanvas(width, height);
+      const ctx = canvas.getContext("2d");
+      const source = new Uint8ClampedArray([
+        255, 0, 0, 255, 0, 255, 0, 255, 0, 0, 255, 255, 255, 255, 0, 255,
+      ]);
+      ctx.putImageData(new ImageData(source, width, height), 0, 0);
+      const bitmap = canvas.transferToImageBitmap();
+      const { imageStream } = await createImage(bitmap, /* xref = */ null, {
+        closeBitmap: true,
+      });
+
+      expect(imageStream.dict.get("Filter").name).toEqual("FlateDecode");
+      const flate = new FlateStream(imageStream, imageStream.length);
+      const predictor = new PredictorStream(
+        flate,
+        imageStream.length,
+        imageStream.dict.get("DecodeParms")
+      );
+      const decoded = predictor.getBytes(width * height * 3);
+      const expected = new Uint8Array(width * height * 3);
+      for (let i = 0, j = 0; i < source.length; i += 4, j += 3) {
+        expected[j] = source[i];
+        expected[j + 1] = source[i + 1];
+        expected[j + 2] = source[i + 2];
+      }
+      expect(decoded).toEqual(expected);
+    });
+  });
+});