chore: import upstream snapshot with attribution

2026-07-13 13:33:03 +08:00
commit 5b57521aa1
8226 changed files with 3425766 additions and 0 deletions
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+//
+//  ImageDatasetDemo.cpp
+//  MNN
+//
+//  Created by MNN on 2019/11/20.
+//  Copyright © 2018, Alibaba Group Holding Limited
+//
+
+#include <iostream>
+#include "DataLoader.hpp"
+#include "DemoUnit.hpp"
+#include "ImageDataset.hpp"
+#include "RandomSampler.hpp"
+#include "Sampler.hpp"
+#include "Transform.hpp"
+#include "TransformDataset.hpp"
+
+#ifdef MNN_USE_OPENCV
+#include <opencv2/opencv.hpp> // use opencv to show pictures
+using namespace cv;
+#endif
+
+using namespace std;
+using namespace MNN;
+using namespace MNN::Train;
+
+/*
+ * this is an demo for how to use the ImageDataset and DataLoader
+ */
+
+class ImageDatasetDemo : public DemoUnit {
+public:
+    // this function is an example to use the lambda transform
+    // here we use lambda transform to normalize data from 0~255 to 0~1
+    static Example func(Example example) {
+        // // an easier way to do this
+        auto cast       = _Cast(example.first[0], halide_type_of<float>());
+        example.first[0] = _Multiply(cast, _Const(1.0f / 255.0f));
+        return example;
+    }
+
+    virtual int run(int argc, const char* argv[]) override {
+        if (argc != 3) {
+            cout << "usage: ./runTrainDemo.out ImageDatasetDemo path/to/images/ path/to/image/txt\n" << endl;
+
+            cout << "the ImageDataset read stored images as input data.\n"
+                    "use 'pathToImages' and a txt file to construct a ImageDataset.\n"
+                    "the txt file should use format as below:\n"
+                    "     image1.jpg label1,label2,...\n"
+                    "     image2.jpg label3,label4,...\n"
+                    "     ...\n"
+                    "the ImageDataset would read images from:\n"
+                    "     pathToImages/image1.jpg\n"
+                    "     pathToImages/image2.jpg\n"
+                    "     ...\n"
+                 << endl;
+
+            return 0;
+        }
+
+        std::string pathToImages   = argv[1];
+        std::string pathToImageTxt = argv[2];
+
+        auto converImagesToFormat  = CV::RGB;
+        int resizeHeight           = 224;
+        int resizeWidth            = 224;
+        std::vector<float> scales = {1/255.0f, 1/255.0f, 1/255.0f};
+        std::shared_ptr<ImageDataset::ImageConfig> config(ImageDataset::ImageConfig::create(converImagesToFormat, resizeHeight, resizeWidth, scales));
+        bool readAllImagesToMemory = false;
+        auto dataset = ImageDataset::create(pathToImages, pathToImageTxt, config.get(), readAllImagesToMemory);
+
+        const int batchSize  = 1;
+        const int numWorkers = 1;
+
+        auto dataLoader = dataset.createLoader(batchSize, true, false, numWorkers);
+
+        const size_t iterations =dataLoader->iterNumber();
+
+        for (int i = 0; i < iterations; i++) {
+            auto trainData = dataLoader->next();
+
+            auto data  = trainData[0].first[0]->readMap<float_t>();
+            auto label = trainData[0].second[0]->readMap<int32_t>();
+
+            cout << "index: " << i << " label: " << int(label[0]) << endl;
+
+#ifdef MNN_USE_OPENCV
+            // only show the first picture in the batch
+            Mat image = Mat(resizeHeight, resizeWidth, CV_32FC(3), (void*)data);
+            imshow("image", image);
+
+            waitKey(-1);
+#endif
+        }
+        // this will reset the sampler's internal state
+        dataLoader->reset();
+        return 0;
+    }
+};
+
+DemoUnitSetRegister(ImageDatasetDemo, "ImageDatasetDemo");