// Halide tutorial lesson 2: Processing images
// Halide入門教程第二講：處理影象

// This lesson demonstrates how to pass in input images and manipulate them.
// 本課說明了如何讀入及處理影象

// On linux, you can compile and run it like so:
// 在linux下，你可以按照如下方式編譯和執行程式碼
// 執行之前確保作業系統安裝了libpng和libjpeg庫，可以到對應的sourceforge上找到對應的程式碼
// 編譯安裝,或者採用linux系統的包管理系統進行安裝:
// sudo apt-get install libpng
// sudo apt-get install libjpeg
// g++ lesson_02*.cpp -g -I ../include -I ../tools -L ../bin -lHalide `libpng-config --cflags --ldflags` -ljpeg -lpthread -ldl -o lesson_02 -std=c++11
// LD_LIBRARY_PATH=../bin ./lesson_02

// On os x:
// g++ lesson_02*.cpp -g -I ../include -I ../tools -L ../bin -lHalide `libpng-config --cflags --ldflags` -ljpeg -o lesson_02 -std=c++11
// DYLD_LIBRARY_PATH=../bin ./lesson_03

// If you have the entire Halide source tree, you can also build it by
// running:
//    make tutorial_lesson_02_input_image
// in a shell with the current directory at the top of the halide
// source tree.

// The only Halide header file you need is Halide.h. It includes all of Halide.
#include "Halide.h"

// Include some support code for loading pngs.
// halide_image_io.h提供了png格式圖片的讀寫程式碼
#include "halide_image_io.h"
using namespace Halide::Tools;

int main(int argc, char **argv) {

    // This program defines a single-stage imaging pipeline that
    // brightens an image.
    // 該程式定義了一級流水級的影象處理流水線來提升影象亮度

    // First we'll load the input image we wish to brighten.
    // halide_image_io.h提供的影象IO函式，讀入要處理的影象資料，
    // 所讀入的影象為8位無符號數。
    Halide::Buffer<uint8_t> input = load_image("images/rgb.png");

    // See figures/lesson_02_input.jpg for a smaller version.

    // Next we define our Func object that represents our one pipeline
    // stage.
    // 接下來定義Func函式物件來表示我們的一級影象處理流水級。
    Halide::Func brighter;

    // Our Func will have three arguments, representing the position
    // in the image and the color channel. Halide treats color
    // channels as an extra dimension of the image.
    // Func將有三個引數，即影象畫素的索引變數，分別為：
    // x，y為座標索引，c為RGB顏色通道索引。
    Halide::Var x, y, c;

    // Normally we'd probably write the whole function definition on
    // one line. Here we'll break it apart so we can explain what
    // we're doing at every step.

    // For each pixel of the input image.
    // value表示式表示c通道（x，y）座標處的畫素值
    Halide::Expr value = input(x, y, c);

    // Cast it to a floating point value.
    // 為了進行浮點計算，先將資料型別轉換成單精度浮點型別
    value = Halide::cast<float>(value);

    // Multiply it by 1.5 to brighten it. Halide represents real
    // numbers as floats, not doubles, so we stick an 'f' on the end
    // of our constant.
    // 將c通道（x，y）座標處的畫素值乘1.5來提升亮度
    value = value * 1.5f;

    // Clamp it to be less than 255, so we don't get overflow when we
    // cast it back to an 8-bit unsigned int.
    // 為了防止資料溢位，將放大後的畫素值限制在[0,255]區間（又稱飽和處理），並轉換成8位無符號整型
    value = Halide::min(value, 255.0f);

    // Cast it back to an 8-bit unsigned integer.
    value = Halide::cast<uint8_t>(value);

    // Define the function.
    // 定義函式，即將亮度提升後的畫素值，賦值給函式物件的（x，y，c）點
    brighter(x, y, c) = value;

    // The equivalent one-liner to all of the above is:
    // 以上函式的定義可用一行來表示：
    // brighter(x, y, c) = Halide::cast<uint8_t>(min(input(x, y, c) * 1.5f, 255));
    //
    // In the shorter version:
    // - I skipped the cast to float, because multiplying by 1.5f does
    //   that automatically.
    // - I also used an integer constant as the second argument in the
    //   call to min, because it gets cast to float to be compatible
    //   with the first argument.
    // - I left the Halide:: off the call to min. It's unnecessary due
    //   to Koenig lookup.

    // Remember, all we've done so far is build a representation of a
    // Halide program in memory. We haven't actually processed any
    // pixels yet. We haven't even compiled that Halide program yet.
    // 上述所有操作只是在記憶體中建立Halide程式，告訴Halide怎麼去進行演算法操作，即對演算法進行了定義。
    // 實際上還沒有開始進行任何畫素的處理。甚至Halide程式還沒有進行編譯

    // So now we'll realize the Func. The size of the output image
    // should match the size of the input image. If we just wanted to
    // brighten a portion of the input image we could request a
    // smaller size. If we request a larger size Halide will throw an
    // error at runtime telling us we're trying to read out of bounds
    // on the input image.
    // 現在將實現函式。輸出影象的尺寸必須和輸入影象的尺寸相匹配。如果我們只想提高輸入影象部分割槽域
    //畫素點的亮度，可以指定一個小一點的尺寸。如果需要一個更大尺寸的輸出，Halide在執行時會丟擲一個
    //錯誤告訴我們，邊界超出輸入影象。
    Halide::Buffer<uint8_t> output =
        brighter.realize(input.width(), input.height(), input.channels());

    // Save the output for inspection. It should look like a bright parrot.
    // 寫下被處理過的影象
    save_image(output, "brighter.png");

    // See figures/lesson_02_output.jpg for a small version of the output.

    printf("Success!\n");
    return 0;
}