tensorflow-helpers/image.js

Helper functions to use tensorflow in nodejs for transfer learning, image classification, and more

"use strict";
var __createBinding = (this && this.__createBinding) || (Object.create ? (function(o, m, k, k2) {
    if (k2 === undefined) k2 = k;
    var desc = Object.getOwnPropertyDescriptor(m, k);
    if (!desc || ("get" in desc ? !m.__esModule : desc.writable || desc.configurable)) {
      desc = { enumerable: true, get: function() { return m[k]; } };
    }
    Object.defineProperty(o, k2, desc);
}) : (function(o, m, k, k2) {
    if (k2 === undefined) k2 = k;
    o[k2] = m[k];
}));
var __setModuleDefault = (this && this.__setModuleDefault) || (Object.create ? (function(o, v) {
    Object.defineProperty(o, "default", { enumerable: true, value: v });
}) : function(o, v) {
    o["default"] = v;
});
var __importStar = (this && this.__importStar) || (function () {
    var ownKeys = function(o) {
        ownKeys = Object.getOwnPropertyNames || function (o) {
            var ar = [];
            for (var k in o) if (Object.prototype.hasOwnProperty.call(o, k)) ar[ar.length] = k;
            return ar;
        };
        return ownKeys(o);
    };
    return function (mod) {
        if (mod && mod.__esModule) return mod;
        var result = {};
        if (mod != null) for (var k = ownKeys(mod), i = 0; i < k.length; i++) if (k[i] !== "default") __createBinding(result, mod, k[i]);
        __setModuleDefault(result, mod);
        return result;
    };
})();
Object.defineProperty(exports, "__esModule", { value: true });
exports.cropAndResizeImageTensor = exports.calcCropBox = exports.getImageTensorShape = void 0;
exports.loadImageFile = loadImageFile;
exports.cropAndResizeImageFile = cropAndResizeImageFile;
const promises_1 = require("fs/promises");
const tf = __importStar(require("@tensorflow/tfjs-node"));
const tensor_1 = require("./tensor");
const image_utils_1 = require("./image-utils");
var image_utils_2 = require("./image-utils");
Object.defineProperty(exports, "getImageTensorShape", { enumerable: true, get: function () { return image_utils_2.getImageTensorShape; } });
Object.defineProperty(exports, "calcCropBox", { enumerable: true, get: function () { return image_utils_2.calcCropBox; } });
Object.defineProperty(exports, "cropAndResizeImageTensor", { enumerable: true, get: function () { return image_utils_2.cropAndResizeImageTensor; } });
async function loadImageFile(file, options) {
    let content = await (0, promises_1.readFile)(file);
    let tensor = options
        ? tf.node.decodeImage(content, options.channels, options.dtype, options.expandAnimations ?? false)
        : tf.node.decodeImage(content);
    if (options?.crop) {
        tensor = (0, image_utils_1.cropAndResizeImageTensor)({
            imageTensor: tensor,
            width: options.crop.width,
            height: options.crop.height,
            aspectRatio: options.crop.aspectRatio,
        });
    }
    return tensor;
}
async function cropAndResizeImageFile(options) {
    let imageTensor = await loadImageFile(options.srcFile, {
        crop: {
            width: options.width,
            height: options.height,
            aspectRatio: options.aspectRatio,
        },
    });
    let tensor3D = tf.tidy(() => (0, tensor_1.toTensor3D)(imageTensor).mul(255));
    let content = await tf.node.encodeJpeg(tensor3D);
    tf.image.cropAndResize;
    tensor3D.dispose();
    await (0, promises_1.writeFile)(options.destFile, content);
}