Fix android build and do some code refactoring (#3)

* fix android script * fix line break * reformat the code * move CMakeLists.txt to platforms/desktop * remove build folder * remove vs projects ' * added ios project * update readme * update format-code.sh permission
robertwgh · Jul 3, 2018 · 975328a · 975328a
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diff --git a/.clang-format b/.clang-format
@@ -0,0 +1,5 @@
+BasedOnStyle:   LLVM
+IndentWidth:    4
+TabWidth:       4
+BreakBeforeBraces: Stroustrup
+AlwaysBreakTemplateDeclarations: true
diff --git a/.gitignore b/.gitignore
@@ -29,4 +29,10 @@
 # Executables
 *.exe
 *.out
-*.app
+*.app
+
+project.xcworkspace/
+xcuserdata/
+*~
+.history
+xcshareddata/
diff --git a/README.md b/README.md
@@ -1,70 +1,67 @@
-## ezSIFT: An easy-to-use stanalone SIFT library.
-* Original URL: https://sourceforge.net/projects/ezsift
-* github URL: https://github.com/robertwgh/ezSIFT
-
-The SIFT (scale-invariant feature transform) algorithm is considered to be one of the most robust local feature detector and description methods. Most of the open-source SIFT implementations rely on some 3rd-party libraries. Some of them even rely on a few different large libraries. These dependencies make the installation, compilation and usage not easy.
-
-The ezSIFT library provides a standalone and lightweight SIFT implementation written in C/C++. The ezSIFT is self-contained, and does not require any other libraries. So it is easy to use and modify. Besides, the implementation of the ezSIFT is straightforward and easy to read. 
-
-For this project, C/C++ source code, Visual Studio 2010、2012 project files, and Android NDK project files are provided.
-
-### Documentation
-Please read [ezSIFT Wiki page](https://github.com/robertwgh/ezSIFT/wiki) for details.
-
-### Versions
-* Created on 9/16/2013.
-* Modified on 3/27/2015.
-* Uploaded to github.com on 6/26/2018.
-
-### Examples
-I also provide two examples showing how to use this library:
-
-* `examples/feature_extract.cpp`: detect keypoints and extract feature descriptor from a single image.
-* `examples/image_match.cpp`: detect keypoints and extract features from two images and perform feature matching. 
-
-### How to build
-#### For Mac OS
-Follow the following instructions:
-```Bash
-mkdir build
-cd build
-cmake ..
-make
-```
-Then you can find the built binary under `build/bin` directory.
-
-Or, you can use the following instruction to generate Xcode project:
-```Bash
-mkdir build
-cd build
-cmake .. -GXcode
-```
-Then, open `ezsift.xcodeproj` project to build.
-
-#### For Visual Studio 2010/2012 (currently VS project is broken, I will fix them soon.)
-1. Go to `build/vs2010` or `build/vs2012`, open `ezsift.sln`. 
-2. Build solution. 
-3. You will find executable files under `build/vs2010/bin` or `build/vs2012/bin`.
-
-#### For Android NDK native mode
-1. Please install Android NDK package, and add NDK root folder to your system environment PATH. 
-2. Go to `build/android`.
-3. run `./build.sh`
-4. You will find the binaries under `build/android/bin/`.
-5. Connect an Android device to your computer using ADB. Use `install_and_run.sh` to install the binaries and run it on the devices.
-
-### License
-
-    Copyright 2013 Guohui Wang
-
-    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.
+## ezSIFT: An easy-to-use stanalone SIFT library.
+* Original URL: https://sourceforge.net/projects/ezsift
+* github URL: https://github.com/robertwgh/ezSIFT
+
+The SIFT (scale-invariant feature transform) algorithm is considered to be one of the most robust local feature detector and description methods. Most of the open-source SIFT implementations rely on some 3rd-party libraries. Some of them even rely on a few different large libraries. These dependencies make the installation, compilation and usage not easy.
+
+The ezSIFT library provides a standalone and lightweight SIFT implementation written in C/C++. The ezSIFT is self-contained, and does not require any other libraries. So it is easy to use and modify. Besides, the implementation of the ezSIFT is straightforward and easy to read. 
+
+For this project, C/C++ source code, Visual Studio 2010、2012 project files, and Android NDK project files are provided.
+
+### Documentation
+Please read [ezSIFT Wiki page](https://github.com/robertwgh/ezSIFT/wiki) for details.
+
+### Examples
+I also provide two examples showing how to use this library:
+
+* `examples/feature_extract`: detect keypoints and extract feature descriptor from a single image.
+* `examples/image_match`: detect keypoints and extract features from two images and perform feature matching. 
+
+### How to build
+#### For Mac OS
+Follow the following instructions:
+```Bash
+cd platforms/desktop/
+mkdir build
+cd build
+cmake ..
+make
+```
+Then you can find the built binary under `build/bin` directory. Run the two demos like this:
+
+```bash
+./image_match img1.pgm img2.pgm
+./feature_extract img1.pgm
+```
+
+Or, you can use the following instruction to generate Xcode project:
+```Bash
+cd platforms/desktop/
+mkdir build
+cd build
+cmake .. -GXcode
+```
+Then, open `ezsift.xcodeproj` project to build.
+
+#### For Android NDK native mode
+1. Please install Android NDK package, and add NDK root folder to your system environment PATH. 
+2. Go to `platforms/android`.
+3. run `./build.sh`
+4. You will find the binaries under `build/android/bin/`.
+5. Connect an Android device to your computer using ADB. Use `install_and_run.sh` to install the binaries and run it on the devices.
+
+### License
+
+    Copyright 2013 Guohui Wang
+
+    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.
diff --git a/examples/feature_extract/feature_extract.cpp b/examples/feature_extract/feature_extract.cpp
@@ -1,63 +1,64 @@
-/*  Copyright (c) 2013, Robert Wang, email: robertwgh (at) gmail.com
-    All rights reserved. https://github.com/robertwgh/ezSIFT
-
-    Description: Detect keypoints and extract descriptors from an input image.
-
-    Revision history:
-        September 15th, 2013: initial version.
-        July 2nd, 2018: code refactor.
-*/
-
-#include "ezsift.h"
-
-#include <iostream>
-#include <list>
-
-#define USE_FIX_FILENAME    0
-int main(int argc, char * argv[])
-{
-
-#if USE_FIX_FILENAME
-    char *file1 = "img1.pgm";
-#else
-    if (argc != 2)
-    {
-        std::cerr << "Please input an input image name.\nUsage: feature_extract img" << std::endl;
-        return -1;
-    }
-    char file1[255];
-    memcpy(file1, argv[1], sizeof(char) * strlen(argv[1]));
-    file1[strlen(argv[1])] = 0;
-#endif
-
-    ezsift::Image<unsigned char> image;
-    if(ezsift::read_pgm(file1, image.data, image.w, image.h)!=0)
-    {
-        std::cerr << "Failed to open input image." << std::endl;
-        return -1;
-    }
-    std::cout << "Image size: " << image.w << "x" << image.h << std::endl;
-
-    bool bExtractDescriptor = true;
-    std::list<ezsift::SiftKeypoint> kpt_list;
-
-    // Double the original image as the first octive.
-    ezsift::double_original_image(true);
-
-    // Perform SIFT computation on CPU.
-    std::cout << "Start SIFT detection ..." << std::endl;
-    ezsift::sift_cpu(image, kpt_list, bExtractDescriptor);
-
-    // Generate output image with keypoints drawing
-    char filename[255];
-    sprintf(filename, "%s_sift_output.ppm", file1);
-    ezsift::draw_keypoints_to_ppm_file(filename, image, kpt_list);
-
-    // Generate keypoints list
-    sprintf(filename, "%s_sift_key.key", file1);
-    ezsift::export_kpt_list_to_file(filename, kpt_list, bExtractDescriptor);
-
-    std::cout << "\nTotal keypoints number: \t\t" << static_cast<unsigned int>(kpt_list.size()) << std::endl;
-
-    return 0;
-}
+/*  Copyright (c) 2013, Robert Wang, email: robertwgh (at) gmail.com
+    All rights reserved. https://github.com/robertwgh/ezSIFT
+
+    Description: Detect keypoints and extract descriptors from an input image.
+
+    Revision history:
+        September 15th, 2013: initial version.
+        July 2nd, 2018: code refactor.
+*/
+
+#include "ezsift.h"
+
+#include <iostream>
+#include <list>
+
+#define USE_FIX_FILENAME 0
+int main(int argc, char *argv[])
+{
+
+#if USE_FIX_FILENAME
+    char *file1 = "img1.pgm";
+#else
+    if (argc != 2) {
+        std::cerr
+            << "Please input an input image name.\nUsage: feature_extract img"
+            << std::endl;
+        return -1;
+    }
+    char file1[255];
+    memcpy(file1, argv[1], sizeof(char) * strlen(argv[1]));
+    file1[strlen(argv[1])] = 0;
+#endif
+
+    ezsift::Image<unsigned char> image;
+    if (ezsift::read_pgm(file1, image.data, image.w, image.h) != 0) {
+        std::cerr << "Failed to open input image." << std::endl;
+        return -1;
+    }
+    std::cout << "Image size: " << image.w << "x" << image.h << std::endl;
+
+    bool bExtractDescriptor = true;
+    std::list<ezsift::SiftKeypoint> kpt_list;
+
+    // Double the original image as the first octive.
+    ezsift::double_original_image(true);
+
+    // Perform SIFT computation on CPU.
+    std::cout << "Start SIFT detection ..." << std::endl;
+    ezsift::sift_cpu(image, kpt_list, bExtractDescriptor);
+
+    // Generate output image with keypoints drawing
+    char filename[255];
+    sprintf(filename, "%s_sift_output.ppm", file1);
+    ezsift::draw_keypoints_to_ppm_file(filename, image, kpt_list);
+
+    // Generate keypoints list
+    sprintf(filename, "%s_sift_key.key", file1);
+    ezsift::export_kpt_list_to_file(filename, kpt_list, bExtractDescriptor);
+
+    std::cout << "\nTotal keypoints number: \t\t"
+              << static_cast<unsigned int>(kpt_list.size()) << std::endl;
+
+    return 0;
+}