├── .gitignore
├── LICENCE
├── README.md
├── config
├── boost.pc.example
├── caffe.pc.example
├── cuda.pc.example
├── dlib-1.pc.example
└── opencv.pc.example
├── cpp
├── README.md
├── makefile
└── src
│ ├── ImageTracker.cpp
│ ├── ImageTracker.h
│ ├── detector
│ ├── Detector.cpp
│ ├── Detector.h
│ ├── RandomDetector.cpp
│ ├── RandomDetector.h
│ ├── SSDDetector.cpp
│ └── SSDDetector.h
│ ├── examples
│ ├── DetectAndTrackDemo.cpp
│ ├── DetectDemo.cpp
│ └── TrackDemo.cpp
│ ├── tracker
│ ├── Affinity.cpp
│ ├── Affinity.h
│ ├── PAOT.cpp
│ ├── PAOT.h
│ ├── RandomTracker.cpp
│ ├── RandomTracker.h
│ ├── Tracker.cpp
│ ├── Tracker.h
│ └── predictor
│ │ ├── Predictor.cpp
│ │ ├── Predictor.h
│ │ ├── StationaryPredictor.cpp
│ │ ├── StationaryPredictor.h
│ │ ├── kalman
│ │ ├── KalmanPredictor.cpp
│ │ └── KalmanPredictor.h
│ │ └── particle
│ │ ├── Particle.cpp
│ │ ├── Particle.h
│ │ ├── ParticleFilter.cpp
│ │ ├── ParticleFilter.h
│ │ ├── ParticlePredictor.cpp
│ │ └── ParticlePredictor.h
│ └── util
│ ├── BoundingBox.cpp
│ ├── BoundingBox.h
│ ├── Detection.cpp
│ ├── Detection.h
│ ├── DetectionFileParser.cpp
│ ├── DetectionFileParser.h
│ ├── Tracking.cpp
│ └── Tracking.h
├── data
└── seqmaps
│ └── seqmap.txt.example
├── makefile
├── models
└── config
│ └── model_config.txt.example
└── python
├── README.md
├── generate_images.py
└── generate_video.sh
/.gitignore:
--------------------------------------------------------------------------------
1 | #### Project specific ####
2 | data/*
3 | models/*
4 | config/*
5 | external/*
6 | !*.example
7 |
8 | # Python
9 | python/output/
10 |
11 | #### Language ####
12 |
13 | #### C++ ####
14 | *.o
15 | *.out
16 | *.out.dSYM/
17 | *.d/
18 |
19 | #### Python ####
20 | __pycache__/
21 | *.py[cod]
22 | *$py.class
23 |
24 | #### IDE #####
25 | # Clion
26 | cmake-build-debug/
27 | CMakeLists.txt
28 |
29 | # Pycharm
30 | .idea/
--------------------------------------------------------------------------------
/LICENCE:
--------------------------------------------------------------------------------
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535 |
536 | Nothing in this License shall be construed as excluding or limiting
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539 |
540 | 12. No Surrender of Others' Freedom.
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569 |
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621 | END OF TERMS AND CONDITIONS
622 |
623 | How to Apply These Terms to Your New Programs
624 |
625 | If you develop a new program, and you want it to be of the greatest
626 | possible use to the public, the best way to achieve this is to make it
627 | free software which everyone can redistribute and change under these terms.
628 |
629 | To do so, attach the following notices to the program. It is safest
630 | to attach them to the start of each source file to most effectively
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632 | the "copyright" line and a pointer to where the full notice is found.
633 |
634 | {one line to give the program's name and a brief idea of what it does.}
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642 | This program is distributed in the hope that it will be useful,
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647 | You should have received a copy of the GNU General Public License
648 | along with this program. If not, see .
649 |
650 | Also add information on how to contact you by electronic and paper mail.
651 |
652 | If the program does terminal interaction, make it output a short
653 | notice like this when it starts in an interactive mode:
654 |
655 | {project} Copyright (C) {year} {fullname}
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657 | This is free software, and you are welcome to redistribute it
658 | under certain conditions; type `show c' for details.
659 |
660 | The hypothetical commands `show w' and `show c' should show the appropriate
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663 |
664 | You should also get your employer (if you work as a programmer) or school,
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666 | For more information on this, and how to apply and follow the GNU GPL, see
667 | .
668 |
669 | The GNU General Public License does not permit incorporating your program
670 | into proprietary programs. If your program is a subroutine library, you
671 | may consider it more useful to permit linking proprietary applications with
672 | the library. If this is what you want to do, use the GNU Lesser General
673 | Public License instead of this License. But first, please read
674 | .
675 |
--------------------------------------------------------------------------------
/README.md:
--------------------------------------------------------------------------------
1 | # tracking-by-detection
2 | Code for my master thesis, titled "Real-Time Multiple Object Tracking: A Study on the Importance of Speed".
3 |
4 | ## Introduction
5 | In this project, we implement a multiple object tracker, following the _tracking-by-detection_ paradigm, as an extension of an existing method. It works by modelling the movement of objects by solving the filtering problem, and associating detections with predicted new locations in new frames using the Hungarian algorithm. Three different similarity measures are used, which use the location and shape of the bounding boxes. Compared to other trackers on the [MOTChallenge](https://motchallenge.net/) leaderboard, our method, referred to as _C++SORT_, is the fastest non-anonymous submission, while also achieving decent score on other metrics. By running our model on the [Okutama-Action](http://okutama-action.org/) dataset, sampled at different frame-rates, we show that the performance is greatly reduced when running the model - including detecting objects - in real-time. In most metrics, the score is reduced by 50%, but in certain cases as much as 90%. We argue that this indicates that other, slower methods could not be used for tracking in real-time, but that more research is required specifically on this.
6 |
7 | This work constitutes my master thesis. The thesis is published [on a university portal](http://www.diva-portal.org/smash/record.jsf?pid=diva2:1146388), but is also made avalable [on arXiv](https://arxiv.org/abs/1709.03572).
8 |
9 | ## Citing
10 | If you find the thesis or this repository useful in your research, please consider citing the report:
11 | ```
12 | @article{murray2017real,
13 | title={Real-Time Multiple Object Tracking - A Study on the Importance of Speed},
14 | author={Murray, Samuel},
15 | journal={arXiv preprint arXiv:1709.03572},
16 | year = {2017}
17 | }
18 | ```
19 |
20 | ## Dependencies
21 | * Build:
22 | * C++11
23 | * make
24 | * pkg-config
25 | * Tracking:
26 | * dlib (≥19.4)
27 | * Detection:
28 | * OpenCV (≥3.2)
29 | * Caffe\*
30 | * Cuda\* (≥7)
31 | * Run demos:
32 | * Boost (≥1.63)
33 |
34 | \* For instructions on how to install `Caffe` and `Cuda`, see **Configure**.
35 |
36 | #### Mac
37 | Use [Homebrew](https://brew.sh/) to build packages.
38 |
39 | To install `OpenCV`, follow [this tutorial](http://www.pyimagesearch.com/2016/12/19/install-opencv-3-on-macos-with-homebrew-the-easy-way/).
40 |
41 | Remaining dependencies can be installed with:
42 | ```
43 | $ brew install
44 | ```
45 |
46 | It might be possible to build all packages yourself, without `Homebrew`. Please refer to the instructions for **Linux** below.
47 |
48 | #### Linux
49 | To install `boost`, see the [official documentation](http://www.boost.org/doc/libs/1_63_0/more/getting_started/unix-variants.html).
50 |
51 | To install `OpenCV`, see the [official documentation](http://docs.opencv.org/master/d7/d9f/tutorial_linux_install.html).
52 |
53 | To install `dlib`, download and unpack it from [here](http://dlib.net/). Build as a shared library with:
54 | ```
55 | $ cd dlib-
56 | $ mkdir build
57 | $ cd build
58 | $ cmake ..
59 | $ make
60 | $ sudo make install
61 | ```
62 |
63 | #### Windows
64 | Not tested. Please refer to the instructions for **Linux** above; some packages have similar guides for Windows.
65 |
66 | ## Configure
67 |
68 | #### Directory structure
69 | The following directories should be present in root:
70 | * `config` - `.pc` files for dependencies.
71 | * `cpp` - C++ source code.
72 | * `data` - Data sets and sequence maps for running demos.
73 | * `models` - Caffe models for object detection.
74 | * `python` - Python scripts for generating images.
75 |
76 | #### pkg-config
77 | Make sure `PKG_CONFIG_PATH` includes the paths to the `.pc` files for all dependencies. Alternatively, copy and modify the `.pc.example` files in `config/`. Test if `pkg-config` can find `.pc` files for all dependencies, including custom ones in `config/`:
78 | ```
79 | $ make test
80 | ```
81 |
82 | #### Caffe
83 | [This version of Caffe](https://github.com/weiliu89/caffe/tree/ssd) is used, which works with SSD models. Thorough instructions are given there on how to install and configure Caffe. They refer to the [official documentation](http://caffe.berkeleyvision.org/installation.html) on how to install prerequisites.
84 |
85 | #### Cuda
86 | See **Caffe** above.
87 |
88 | ## Demo
89 | #### Directory structure
90 | * `data/` - Put datasets (images and/or detections) here. Images are expected to be in `/images/`, and detections in `/model-type` (this is also where custom detections will be put). Sequence maps should exist in `data/seqmaps` (an example file is given). Tracking output will be in `data/result//.txt`.
91 | * `models/` - To use Caffe, put models in `models/`. Config files for each model should exist in `models/config/` (an example file is given).
92 |
93 | Three example usages are provided:
94 | 1. **Detect** - Detect objects in a provided sequence of images. Objects are detected by a CNN (Caffe).
95 | 1. **Track** - Track objects from provided detections. The detections should be on the format used in [MOTChallenge](https://motchallenge.net/).
96 | 1. **Detect and Track** - Track objects detected in a provided sequence of images. Objects are detected by a CNN (Caffe).
97 |
98 | ## Integrate in other projects
99 | All source code is in `cpp/src/`.
100 | * To track objects from pre-existing detections, create an instance of `MCSORT`. No code in `detector/` is needed. Use function `tracker.track()`.
101 | * To detect and track objects from images, create an instance of `ImageTracker`. Requires Caffe. Use function `tracker.detectAndTrack()`.
102 |
--------------------------------------------------------------------------------
/config/boost.pc.example:
--------------------------------------------------------------------------------
1 | # Package Information for pkg-config
2 |
3 | # Path to where Boost is installed
4 | prefix=/path/to/boost
5 | # Path to where libraries are
6 | libdir=${prefix}/lib
7 | # Path to where include files are
8 | includedir=${prefix}/include
9 |
10 | Name: Boost
11 | Description: Boost provides free peer-reviewed portable C++ source libraries
12 | Version: 1.63.0
13 | Libs: -L${libdir} -lboost_filesystem -lboost_system
14 | Cflags: -isystem ${includedir}
--------------------------------------------------------------------------------
/config/caffe.pc.example:
--------------------------------------------------------------------------------
1 | # Package Information for pkg-config
2 |
3 | # Path to where Caffe is installed
4 | prefix=/path/to/caffe
5 | # Path to where libraries are
6 | libdir=${prefix}/.build_release/lib
7 | # Path to where include files are
8 | includedir=${prefix}/include
9 |
10 | Name: Caffe
11 | Description: Deep learning framework by the BVLC
12 | Version: 1.0
13 | Libs: -L${libdir} -lcaffe
14 | Cflags: -isystem${includedir} -isystem${prefix}/.build_release/src
--------------------------------------------------------------------------------
/config/cuda.pc.example:
--------------------------------------------------------------------------------
1 | # Package Information for pkg-config
2 |
3 | # Path to where CUDA is installed
4 | prefix=/path/to/cuda
5 | # Path to where include files are
6 | includedir=${prefix}/include
7 |
8 | Name: CUDA
9 | Description: A parallel computing platform and programming model invented by NVIDIA
10 | Version: 7.0
11 | Cflags: -isystem ${includedir}
12 | Libs: -lboost_system -lglog -lgflags
--------------------------------------------------------------------------------
/config/dlib-1.pc.example:
--------------------------------------------------------------------------------
1 | # Package Information for pkg-config
2 |
3 | # Path to where dlib is installed
4 | prefix=/path/to/dlib
5 | # Path to where libraries are
6 | libdir=${prefix}/lib
7 | # Path to where include files are
8 | includedir=${prefix}/include
9 |
10 | Name: dlib
11 | Description: Numerical and networking C++ library
12 | Version: 19.4.0
13 | Libs: -L${libdir} -ldlib
14 | Cflags: -isystem${includedir}
15 | Requires: libpng
--------------------------------------------------------------------------------
/config/opencv.pc.example:
--------------------------------------------------------------------------------
1 | # Package Information for pkg-config
2 |
3 | # Path to where OpenCV is installed
4 | prefix=/path/to/opencv3
5 | # Path to where libraries is
6 | libdir=${prefix}/lib
7 | # Path to where include files are
8 | includedir_old=${prefix}/include/opencv
9 | includedir_new=${prefix}/include
10 |
11 | Name: OpenCV
12 | Description: Open Source Computer Vision Library
13 | Version: 3.2.0
14 | Libs: -L${prefix}/lib -lopencv_stitching -lopencv_superres -lopencv_videostab -lopencv_aruco -lopencv_bgsegm -lopencv_bioinspired -lopencv_ccalib -lopencv_dpm -lopencv_fuzzy -lopencv_hdf -lopencv_line_descriptor -lopencv_optflow -lopencv_reg -lopencv_saliency -lopencv_stereo -lopencv_structured_light -lopencv_phase_unwrapping -lopencv_rgbd -lopencv_surface_matching -lopencv_tracking -lopencv_datasets -lopencv_text -lopencv_face -lopencv_plot -lopencv_dnn -lopencv_xfeatures2d -lopencv_shape -lopencv_video -lopencv_ximgproc -lopencv_calib3d -lopencv_features2d -lopencv_flann -lopencv_xobjdetect -lopencv_objdetect -lopencv_ml -lopencv_xphoto -lopencv_highgui -lopencv_videoio -lopencv_imgcodecs -lopencv_photo -lopencv_imgproc -lopencv_core
15 | Cflags: -I${includedir_old} -I${includedir_new}
--------------------------------------------------------------------------------
/cpp/README.md:
--------------------------------------------------------------------------------
1 | # C++
2 | The source code of the project. Code is located in `src/`.
3 |
4 | ## Compile
5 | Compile everything:
6 | ```
7 | $ make compile [use_caffe=true] [force_rebuild=true]
8 | ```
9 |
10 | Remove all created files:
11 | ```
12 | $ make clean
13 | ```
14 |
15 | Check the value of a makefile variable:
16 | ```
17 | $ make print-
18 | ```
19 |
20 | **NOTE:** Calling `make ` without passing `use_caffe=true` will make the preprocessor remove all code that uses Caffe. This is to enable compilation without Caffe installed. However, this can lead to problems when _e.g._ `make detect use_caffe=true` is called after `make track`, since the files that use Caffe will not be rebuilt. To prevent this, either pass `use_caffe=true` every time you compile, or call `force_rebuild=true` to force all `.o` files to be rebuilt.
21 |
22 | ## Demo
23 | Two example usages are provided. Note that the following targets will also compile the code, and so the same variables (`use_caffe` and `force_rebuild`) are used.
24 | Three example usages are provided:
25 | 1. **Detect** - Detect objects in a provided sequence of images. Objects are detected by a CNN (Caffe).
26 | ```
27 | $ make detect
28 | $ ./detectApp.out [-s sequencesFile] [-m modelConfigFile]
29 | ```
30 | 2. **Track** - Track objects from provided detections. The detections should be on the format used in [MOTChallenge](https://motchallenge.net/).
31 | ```
32 | $ make track
33 | $ ./trackApp.out [-s sequencesFile] [-m modelType] \
34 | [-d detectionFormat] [-i frameInterval]
35 | ```
36 |
37 | 3. **Detect and Track** - Track objects detected in a provided sequence of images. Objects are detected by a CNN (Caffe).
38 | ```
39 | $ make detectAndTrack
40 | $ ./trackApp.out [-s sequencesFile] [-m modelConfigFile]
41 | ```
42 |
43 | ## Integrate in other projects
44 | * To detect objects from images, create an instance of `SSDDetector`. Requires Caffe. Use function `detector.detect()`.
45 | * To track objects from pre-existing detections, create an instance of `PAOT`. No code in `detector/` is needed. Use function `tracker.track()`.
46 | * To detect and track objects from images, create an instance of `ImageTracker`. Requires Caffe. Use function `tracker.detectAndTrack()`.
47 |
--------------------------------------------------------------------------------
/cpp/makefile:
--------------------------------------------------------------------------------
1 | SHELL = /bin/sh
2 |
3 | # Compiler options
4 | CXX = g++
5 | CXXFLAGS = -std=c++11 -g -Wall -pedantic
6 | LDFLAGS =
7 | DEPFLAGS = -MT $@ -MMD -MP -MF $(DEPDIR)/$*.Td
8 |
9 | # External libraries
10 | export PKG_CONFIG_PATH := ../config:$(PKG_CONFIG_PATH)
11 |
12 | # OpenCV
13 | CXXFLAGS += `pkg-config --cflags opencv`
14 | LDFLAGS += `pkg-config --libs opencv`
15 |
16 | # dlib
17 | CXXFLAGS += `pkg-config --cflags dlib-1`
18 | LDFLAGS += `pkg-config --libs dlib-1`
19 |
20 | # Boost
21 | CXXFLAGS += `pkg-config --cflags boost`
22 | LDFLAGS += `pkg-config --libs boost`
23 |
24 | # For compilation with Caffe
25 | use_caffe = false
26 | ifeq ($(use_caffe),true)
27 | # Caffe
28 | CXXFLAGS += -DUSE_CAFFE
29 | CXXFLAGS += `pkg-config --cflags caffe`
30 | LDFLAGS += `pkg-config --libs caffe`
31 |
32 | # Cuda
33 | CXXFLAGS += `pkg-config --cflags cuda`
34 | LDFLAGS += `pkg-config --libs cuda`
35 | endif
36 |
37 | # Directories
38 | SOURCEDIR = src
39 | BUILDDIR = build
40 | MAINDIR = examples
41 | DEPDIR = .d
42 |
43 | # Input/Output files
44 | SOURCES := $(shell find $(SOURCEDIR) -name "*.cpp")
45 | OBJECTS := $(patsubst $(SOURCEDIR)/%.cpp,$(BUILDDIR)/%.o,$(SOURCES))
46 | DEPFILES := $(patsubst $(SOURCEDIR)/%.cpp,$(DEPDIR)/%.d,$(SOURCES))
47 | TARGET_detect := detectApp.out
48 | TARGET_track := trackApp.out
49 | TARGET_detectAndTrack := detectAndTrackApp.out
50 | TARGETS := $(TARGET_detect) $(TARGET_track) $(TARGET_detectAndTrack)
51 |
52 | # For running DetectDemo.cpp
53 | OBJECTS_detect := $(filter-out $(BUILDDIR)/$(MAINDIR)/%.o,$(OBJECTS))
54 | OBJECTS_detect += $(BUILDDIR)/$(MAINDIR)/DetectDemo.o
55 |
56 | # For running TrackDemo.cpp
57 | OBJECTS_track := $(filter-out $(BUILDDIR)/$(MAINDIR)/%.o,$(OBJECTS))
58 | OBJECTS_track += $(BUILDDIR)/$(MAINDIR)/TrackDemo.o
59 |
60 | # For running DetectAndTrackDemo.cpp
61 | OBJECTS_detectAndTrack := $(filter-out $(BUILDDIR)/$(MAINDIR)/%.o,$(OBJECTS))
62 | OBJECTS_detectAndTrack += $(BUILDDIR)/$(MAINDIR)/DetectAndTrackDemo.o
63 |
64 | # Build instructioncs
65 | MKDIRIFNOTEXIST = @test -d $(@D) || mkdir -p $(@D)
66 | COMPILE = $(CXX) $(DEPFLAGS) $(CXXFLAGS) -c
67 | POSTCOMPILE = mv -f $(DEPDIR)/$*.Td $(DEPDIR)/$*.d
68 |
69 | # Targets
70 | .SECONDEXPANSION:
71 |
72 | # Instructions
73 | all:
74 | @echo 'Call "make compile" to compile everything, or "make " to compile and link a specific target'
75 |
76 | # Print variable
77 | print-% : ; @echo $* = $($*)
78 |
79 | # Compile and link target
80 | detect track detectAndTrack: compile $$(TARGET_$$@)
81 |
82 | # Link target's objects
83 | %App.out: $$(OBJECTS_%)
84 | @echo '(link) CXX $@'
85 | @$(CXX) -o $@ $^ $(LDFLAGS)
86 |
87 | # Compile all files
88 | compile: $(OBJECTS)
89 |
90 | # Crazy alternative: [...]%.d | $(BUILDDIR)/$$(filter-out ./,$$(dir %)).dir --- %.dir: ; $(MKDIRIFNOTEXIST)
91 | $(BUILDDIR)/%.o: $(SOURCEDIR)/%.cpp $(DEPDIR)/%.d
92 | @echo '(compile) CXX $<'
93 | @$(MKDIRIFNOTEXIST)
94 | @$(COMPILE) $< -o $@
95 | @$(POSTCOMPILE)
96 |
97 | $(DEPDIR)/%.d:
98 | $(MKDIRIFNOTEXIST)
99 |
100 | # Prevent files from being deleted as intermediate files by make
101 | .PRECIOUS: $(OBJECTS) $(DEPFILES)
102 |
103 | # Include dependency files
104 | include $(wildcard $(DEPFILES))
105 |
106 | # Rebuild all object files
107 | force_rebuild = false
108 | ifeq ($(force_rebuild),true)
109 | $(shell rm $(OBJECTS))
110 | endif
111 |
112 | # Remove all generated files
113 | .PHONY: clean
114 | clean:
115 | rm -f $(OBJECTS)
116 | rm -f $(DEPFILES)
117 | rm -f $(TARGETS)
--------------------------------------------------------------------------------
/cpp/src/ImageTracker.cpp:
--------------------------------------------------------------------------------
1 | #include "ImageTracker.h"
2 |
3 | ImageTracker::ImageTracker(const std::shared_ptr &detector, const std::shared_ptr &tracker)
4 | : detector(detector), tracker(tracker) {}
5 |
6 | std::vector ImageTracker::detectAndTrack(const cv::Mat &image) const {
7 | return tracker->track(detector->detect(image));
8 | }
--------------------------------------------------------------------------------
/cpp/src/ImageTracker.h:
--------------------------------------------------------------------------------
1 | #ifndef CPP_IMAGETRACKER_H
2 | #define CPP_IMAGETRACKER_H
3 |
4 |
5 | #include "detector/Detector.h"
6 | #include "tracker/Tracker.h"
7 |
8 | #include
9 |
10 | class ImageTracker {
11 | public:
12 | ImageTracker(const std::shared_ptr &detector, const std::shared_ptr &tracker);
13 |
14 | /**
15 | * For each frame, gets a set of Detections from Detector and tracks them with Tracker.
16 | * Returns the Trackings.
17 | */
18 | std::vector detectAndTrack(const cv::Mat &image) const;
19 |
20 | private:
21 | std::shared_ptr detector;
22 | std::shared_ptr tracker;
23 | };
24 |
25 |
26 | #endif //CPP_IMAGETRACKER_H
--------------------------------------------------------------------------------
/cpp/src/detector/Detector.cpp:
--------------------------------------------------------------------------------
1 | #include "Detector.h"
--------------------------------------------------------------------------------
/cpp/src/detector/Detector.h:
--------------------------------------------------------------------------------
1 | #ifndef CPP_DETECTOR_H
2 | #define CPP_DETECTOR_H
3 |
4 |
5 | #include "../util/Detection.h"
6 |
7 | #include
8 |
9 | #include
10 |
11 | class Detector {
12 | public:
13 | Detector() = default;
14 |
15 | virtual ~Detector() = default;
16 |
17 | // Prevent copying and moving
18 | Detector(const Detector &) = delete;
19 |
20 | Detector(Detector &&rhs) = delete;
21 |
22 | Detector &operator=(const Detector &) = delete;
23 |
24 | Detector &operator=(Detector &&rhs) = delete;
25 |
26 | /**
27 | * Detects objects in a given image.
28 | * Returns the Detections.
29 | */
30 | virtual std::vector detect(const cv::Mat &image) = 0;
31 | };
32 |
33 |
34 | #endif //CPP_DETECTOR_H
--------------------------------------------------------------------------------
/cpp/src/detector/RandomDetector.cpp:
--------------------------------------------------------------------------------
1 | #include "RandomDetector.h"
2 |
3 | // Methods
4 |
5 | std::vector RandomDetector::detect(const cv::Mat &image) {
6 | std::vector detections;
7 | detections.push_back(Detection(0, 1, BoundingBox(0.1 * image.cols + rand() % 10 - 5,
8 | 0.2 * image.rows + rand() % 10 - 5,
9 | 50,
10 | 50
11 | )));
12 | detections.push_back(Detection(0, 1, BoundingBox(0.4 * image.cols + rand() % 10 - 5,
13 | 0.7 * image.rows + rand() % 10 - 5,
14 | 40,
15 | 100
16 | )));
17 | detections.push_back(Detection(1, 1, BoundingBox(0.8 * image.cols + rand() % 10 - 5,
18 | 0.8 * image.rows + rand() % 10 - 5,
19 | 90,
20 | 30
21 | )));
22 | return detections;
23 | }
--------------------------------------------------------------------------------
/cpp/src/detector/RandomDetector.h:
--------------------------------------------------------------------------------
1 | #ifndef CPP_RANDOMDETECTOR_H
2 | #define CPP_RANDOMDETECTOR_H
3 |
4 |
5 | #include "Detector.h"
6 |
7 | class RandomDetector : public Detector {
8 | public:
9 | RandomDetector() = default;
10 |
11 | /**
12 | * Returns a set of (semi) random Detections, independent of the image.
13 | * Only used as a placeholder for a real Detector, e.g. for debugging.
14 | */
15 | std::vector detect(const cv::Mat &image) override;
16 | };
17 |
18 |
19 | #endif //CPP_RANDOMDETECTOR_H
--------------------------------------------------------------------------------
/cpp/src/detector/SSDDetector.cpp:
--------------------------------------------------------------------------------
1 | #include "SSDDetector.h"
2 |
3 | #ifdef USE_CAFFE
4 |
5 | #include
6 | #include
7 |
8 | using caffe::Caffe;
9 | using caffe::Net;
10 | using caffe::Blob;
11 |
12 | // Constructors
13 |
14 | SSDDetector::SSDDetector(const std::string &modelFile, const std::string &weightsFile, const std::string &meanValue)
15 | : Detector() {
16 | Caffe::set_mode(Caffe::GPU);
17 |
18 | // Load the network.
19 | net.reset(new Net(modelFile, caffe::TEST));
20 | net->CopyTrainedLayersFrom(weightsFile);
21 |
22 | Blob *inputLayer = net->input_blobs()[0];
23 | numChannels = inputLayer->channels();
24 | inputGeometry = cv::Size(inputLayer->width(), inputLayer->height());
25 | setMean(meanValue);
26 | }
27 |
28 | // Methods
29 |
30 | std::vector SSDDetector::detect(const cv::Mat &image) {
31 | Blob *inputLayer = net->input_blobs()[0];
32 | inputLayer->Reshape(1, numChannels, inputGeometry.height, inputGeometry.width);
33 |
34 | // Forward dimension change to all layers.
35 | net->Reshape();
36 | std::vector inputChannels;
37 | wrapInputLayer(&inputChannels);
38 | preprocess(image, &inputChannels);
39 | net->Forward();
40 |
41 | // Copy the output layer to a vector
42 | Blob *resultBlob = net->output_blobs()[0];
43 |
44 | // Result format: [image_id, label, score, xmin, ymin, xmax, ymax].
45 | const float *result = resultBlob->cpu_data();
46 | const int numDet = resultBlob->height();
47 | std::vector detections;
48 | for (int k = 0; k < numDet; ++k) {
49 | if (result[0] == -1 || result[2] < 0.1) {
50 | // Skip invalid detection.
51 | result += 7;
52 | continue;
53 | }
54 | std::vector det(result, result + 7);
55 |
56 | Detection detection(int(det[1]), det[2], BoundingBox((det[3] + det[5]) / 2 * image.cols,
57 | (det[4] + det[6]) / 2 * image.rows,
58 | (det[5] - det[3]) * image.cols,
59 | (det[6] - det[4]) * image.rows
60 | ));
61 |
62 | detections.push_back(detection);
63 | result += 7;
64 | }
65 | return detections;
66 | }
67 |
68 | void SSDDetector::setMean(const std::string &meanValue) {
69 | cv::Scalar channelMean;
70 | std::stringstream ss(meanValue);
71 | std::vector values;
72 | std::string item;
73 | while (getline(ss, item, ',')) {
74 | double value = std::atof(item.c_str());
75 | values.push_back(value);
76 | }
77 |
78 | std::vector channels;
79 | for (int i = 0; i < numChannels; ++i) {
80 | // Extract an individual channel.
81 | cv::Mat channel(inputGeometry.height, inputGeometry.width, CV_32FC1, cv::Scalar(values[i]));
82 | channels.push_back(channel);
83 | }
84 | cv::merge(channels, mean);
85 | }
86 |
87 | void SSDDetector::wrapInputLayer(std::vector *inputChannels) {
88 | Blob *inputLayer = net->input_blobs()[0];
89 |
90 | int width = inputLayer->width();
91 | int height = inputLayer->height();
92 | float *inputData = inputLayer->mutable_cpu_data();
93 | for (int i = 0; i < inputLayer->channels(); ++i) {
94 | cv::Mat channel(height, width, CV_32FC1, inputData);
95 | inputChannels->push_back(channel);
96 | inputData += width * height;
97 | }
98 | }
99 |
100 | void SSDDetector::preprocess(const cv::Mat &image, std::vector *inputChannels) {
101 | // Convert the input image to the input image format of the network.
102 | cv::Mat sample;
103 | if (image.channels() == 3 && numChannels == 1)
104 | cv::cvtColor(image, sample, cv::COLOR_BGR2GRAY);
105 | else if (image.channels() == 4 && numChannels == 1)
106 | cv::cvtColor(image, sample, cv::COLOR_BGRA2GRAY);
107 | else if (image.channels() == 4 && numChannels == 3)
108 | cv::cvtColor(image, sample, cv::COLOR_BGRA2BGR);
109 | else if (image.channels() == 1 && numChannels == 3)
110 | cv::cvtColor(image, sample, cv::COLOR_GRAY2BGR);
111 | else
112 | sample = image;
113 |
114 | cv::Mat sampleResized;
115 | if (sample.size() != inputGeometry)
116 | cv::resize(sample, sampleResized, inputGeometry);
117 | else
118 | sampleResized = sample;
119 |
120 | cv::Mat sampleFloat;
121 | if (numChannels == 3)
122 | sampleResized.convertTo(sampleFloat, CV_32FC3);
123 | else
124 | sampleResized.convertTo(sampleFloat, CV_32FC1);
125 |
126 | cv::Mat sampleNormalized;
127 | cv::subtract(sampleFloat, mean, sampleNormalized);
128 |
129 | /*
130 | * This operation will write the separate BGR planes directly to the
131 | * input layer of the network because it is wrapped by the cv::Mat
132 | * objects in inputChannels.
133 | */
134 | cv::split(sampleNormalized, *inputChannels);
135 | }
136 |
137 | #else //USE_CAFFE
138 |
139 | #include
140 | #include
141 | SSDDetector::SSDDetector() {
142 | std::cerr << "Use of SSDDetector requires Caffe; compile with USE_CAFFE.\n";
143 | throw std::runtime_error("Use of SSDDetector requires Caffe; compile with USE_CAFFE.");
144 | }
145 |
146 | SSDDetector::SSDDetector(const std::string &model_file,
147 | const std::string &weights_file,
148 | const std::string &mean_value) : SSDDetector() {}
149 | std::vector SSDDetector::detect(const cv::Mat &image) {
150 | throw std::runtime_error("Use of SSDDetector requires Caffe; compile with USE_CAFFE.");
151 | }
152 |
153 | #endif //USE_CAFFE
--------------------------------------------------------------------------------
/cpp/src/detector/SSDDetector.h:
--------------------------------------------------------------------------------
1 | #ifndef CPP_SSDDETECTOR_H
2 | #define CPP_SSDDETECTOR_H
3 |
4 |
5 | #include "Detector.h"
6 |
7 | #include
8 |
9 | #ifdef USE_CAFFE
10 |
11 | #include
12 |
13 | #endif //USE_CAFFE
14 |
15 | #include
16 | #include
17 |
18 | #ifdef USE_CAFFE
19 |
20 | class SSDDetector : public Detector {
21 | public:
22 | SSDDetector(const std::string &modelFile, const std::string &weightsFile, const std::string &meanValue);
23 |
24 | std::vector detect(const cv::Mat &image) override;
25 |
26 | private:
27 | void setMean(const std::string &meanValue);
28 |
29 | /**
30 | * Wrap the input layer of the network in separate cv::Mat objects
31 | * (one per channel). This way we save one memcpy operation and we
32 | * don't need to rely on cudaMemcpy2D. The last preprocessing operation
33 | * will write the separate channels directly to the input layer.
34 | */
35 | void wrapInputLayer(std::vector *inputChannels);
36 |
37 | void preprocess(const cv::Mat &image, std::vector *inputChannels);
38 |
39 | std::shared_ptr> net;
40 | cv::Size inputGeometry;
41 | int numChannels;
42 | cv::Mat mean;
43 | };
44 |
45 | #else // USE_CAFFE
46 |
47 | class SSDDetector : public Detector {
48 | public:
49 | SSDDetector();
50 |
51 | SSDDetector(const std::string &model_file, const std::string &weights_file, const std::string &mean_value);
52 |
53 | std::vector detect(const cv::Mat &image) override;
54 | };
55 |
56 | #endif //USE_CAFFE
57 |
58 |
59 | #endif //CPP_SSDDETECTOR_H
--------------------------------------------------------------------------------
/cpp/src/examples/DetectAndTrackDemo.cpp:
--------------------------------------------------------------------------------
1 | #include "../ImageTracker.h"
2 | #include "../detector/RandomDetector.h"
3 | #include "../detector/SSDDetector.h"
4 | #include "../tracker/PAOT.h"
5 |
6 | #include
7 | #include
8 | #include
9 |
10 | #include
11 | #include
12 |
13 | #include
14 | #include
15 | #include
16 | #include
17 | #include
18 | #include
19 |
20 | static const boost::filesystem::path dataDirPath = boost::filesystem::current_path().parent_path() / "data";
21 | static const boost::filesystem::path modelDirPath = boost::filesystem::current_path().parent_path() / "models";
22 | static const double originalFrameRate = 30;
23 |
24 | const char *USAGE_MESSAGE = "Usage: %s "
25 | "-s sequenceMap "
26 | "-m modelConfigFile "
27 | "[-r]\n";
28 | const char *OPEN_FILE_MESSAGE = "Could not open file %s\n";
29 | const char *OPEN_DIR_MESSAGE = "Could not open directory %s\n";
30 | const char *FILE_EXISTS_MESSAGE = "Output file %s already exists; don't overwrite\n";
31 |
32 | std::pair, int> detectAndTrack(const std::shared_ptr &detector,
33 | const boost::filesystem::path &sequencePath,
34 | const std::string &modelType,
35 | const bool realTime) {
36 | typedef std::chrono::duration msduration;
37 |
38 | // Make sure input directory exists
39 | boost::filesystem::path inputDirPath = dataDirPath / sequencePath / "images";
40 | if (!boost::filesystem::is_directory(inputDirPath)) {
41 | fprintf(stderr, OPEN_DIR_MESSAGE, sequencePath.c_str());
42 | exit(EXIT_FAILURE);
43 | }
44 |
45 | // Create output directory if not exists
46 | boost::filesystem::path outputDirPath = dataDirPath / "results" / sequencePath.parent_path() / modelType;
47 | if (!boost::filesystem::is_directory(outputDirPath)) {
48 | boost::filesystem::create_directories(outputDirPath);
49 | }
50 |
51 | // Make sure output file does not exist
52 | boost::filesystem::path outputPath = outputDirPath / (sequencePath.filename().string() + ".txt");
53 | if (boost::filesystem::exists(outputPath)) {
54 | fprintf(stderr, FILE_EXISTS_MESSAGE, outputPath.c_str());
55 | return std::pair(msduration(0), 0);
56 | }
57 |
58 | // Make sure output file can be opened
59 | std::ofstream outputStream;
60 | outputStream.open(outputPath.string());
61 | if (!outputStream.is_open()) {
62 | fprintf(stderr, OPEN_FILE_MESSAGE, outputPath.c_str());
63 | exit(EXIT_FAILURE);
64 | }
65 |
66 | ImageTracker imageTracker(detector, std::make_shared());
67 |
68 | std::vector imagePaths;
69 | std::copy(boost::filesystem::directory_iterator(inputDirPath),
70 | boost::filesystem::directory_iterator(),
71 | std::back_inserter(imagePaths));
72 | std::sort(imagePaths.begin(), imagePaths.end());
73 |
74 | msduration cumulativeDuration = std::chrono::milliseconds::zero();
75 | int frameCount = 0;
76 | int frame = 0;
77 | for (auto imageIt = imagePaths.begin(); imageIt != imagePaths.end(); ++imageIt) {
78 | std::cout << "Image: " << imageIt->string() << std::endl;
79 | cv::Mat image = cv::imread(imageIt->string(), 1);
80 |
81 | auto startTime = std::chrono::high_resolution_clock::now();
82 | std::vector trackings = imageTracker.detectAndTrack(image);
83 | auto endTime = std::chrono::high_resolution_clock::now();
84 | msduration duration = std::chrono::duration_cast(
85 | endTime - startTime);
86 | cumulativeDuration += duration;
87 |
88 | for (auto trackingIt = trackings.begin(); trackingIt != trackings.end(); ++trackingIt) {
89 | outputStream << frame << ","
90 | << trackingIt->ID << ","
91 | << trackingIt->bb.x1() << ","
92 | << trackingIt->bb.y1() << ","
93 | << trackingIt->bb.width << ","
94 | << trackingIt->bb.height << ","
95 | << "1" << "," // Confidence
96 | << "-1,-1,-1" << "," // Unused
97 | << trackingIt->label << "\n";
98 | }
99 | if (realTime) {
100 | int framesToSkip = int((originalFrameRate * duration.count()) / 1000) - 1;
101 | std::cout << "Skipping " << framesToSkip << " frames" << std::endl;
102 | for (int i = 0; i < framesToSkip; ++i) {
103 | if (imageIt == imagePaths.end()) {
104 | ++frameCount;
105 | outputStream.close();
106 | return std::pair(cumulativeDuration, frameCount);
107 | }
108 | ++frame;
109 | ++imageIt;
110 | }
111 | }
112 | ++frame;
113 | ++frameCount;
114 | if (frameCount % 100 == 0) {
115 | std::cout << "Processed " << frameCount << " images" << std::endl;
116 | }
117 | }
118 | outputStream.close();
119 | return std::pair(cumulativeDuration, frameCount);
120 | }
121 |
122 | #ifdef USE_CAFFE
123 |
124 | int main(int argc, char **argv) {
125 |
126 | std::string sequenceMapName;
127 | std::string modelConfigFileName;
128 | std::string modelType;
129 | bool realTime = false;
130 | std::shared_ptr detector;
131 |
132 | int opt;
133 | while ((opt = getopt(argc, argv, "s:m:r")) != -1) {
134 | switch (opt) {
135 | case 's':
136 | sequenceMapName = optarg;
137 | break;
138 | case 'm':
139 | modelConfigFileName = optarg;
140 | break;
141 | case 'r':
142 | realTime = true;
143 | break;
144 | default:
145 | fprintf(stderr, USAGE_MESSAGE, argv[0]);
146 | exit(EXIT_FAILURE);
147 | }
148 | }
149 | if (sequenceMapName == "" || modelConfigFileName == "") {
150 | fprintf(stderr, USAGE_MESSAGE, argv[0]);
151 | exit(EXIT_FAILURE);
152 | }
153 |
154 | boost::filesystem::path modelConfigFilePath = modelDirPath / "config" / modelConfigFileName;
155 | std::ifstream modelConfigFile(modelConfigFilePath.string());
156 | if (modelConfigFile.is_open()) {
157 | std::string modelFile;
158 | std::string weightsFile;
159 | std::string meanValues;
160 | std::getline(modelConfigFile, modelType);
161 | std::getline(modelConfigFile, modelFile);
162 | std::getline(modelConfigFile, weightsFile);
163 | std::getline(modelConfigFile, meanValues);
164 | boost::filesystem::path modelFilePath = modelDirPath / modelFile;
165 | boost::filesystem::path weightsFilePath = modelDirPath / weightsFile;
166 | detector = std::make_shared(modelFilePath.string(), weightsFilePath.string(), meanValues);
167 | } else {
168 | fprintf(stderr, OPEN_FILE_MESSAGE, modelConfigFilePath.c_str());
169 | exit(EXIT_FAILURE);
170 | }
171 |
172 | boost::filesystem::path sequenceMapPath = dataDirPath / "seqmaps" / sequenceMapName;
173 | std::ifstream sequenceMap(sequenceMapPath.string());
174 | if (sequenceMap.is_open()) {
175 |
176 | std::chrono::duration cumulativeDuration;
177 | int cumulativeFrameCount = 0;
178 |
179 | std::string sequencePathString;
180 | while (std::getline(sequenceMap, sequencePathString)) {
181 | std::cout << "Sequence: " << sequencePathString << std::endl;
182 | auto durationFrameCount = detectAndTrack(detector, sequencePathString, modelType, realTime);
183 | auto duration = std::chrono::duration_cast(durationFrameCount.first).count();
184 | std::cout << "Duration: " << duration << "ms"
185 | << " (" << double(durationFrameCount.second * 1000) / duration << "fps)\n";
186 | cumulativeDuration += durationFrameCount.first;
187 | cumulativeFrameCount += durationFrameCount.second;
188 | }
189 | sequenceMap.close();
190 | auto totalDuration = std::chrono::duration_cast(cumulativeDuration).count();
191 | std::cout << "Total duration: " << double(totalDuration) / 1000 << "s"
192 | << " (" << double(cumulativeFrameCount * 1000) / totalDuration << "fps)\n";
193 | } else {
194 | fprintf(stderr, OPEN_FILE_MESSAGE, sequenceMapName.c_str());
195 | exit(EXIT_FAILURE);
196 | }
197 | exit(EXIT_SUCCESS);
198 | }
199 |
200 | #else //USE_CAFFE
201 | int main(int argc, char** argv) {
202 | std::cerr << "This example requires Caffe; compile with USE_CAFFE.\n";
203 | exit(EXIT_FAILURE);
204 | }
205 | #endif //USE_CAFFE
--------------------------------------------------------------------------------
/cpp/src/examples/DetectDemo.cpp:
--------------------------------------------------------------------------------
1 | #include "../detector/RandomDetector.h"
2 | #include "../detector/SSDDetector.h"
3 |
4 | #include
5 | #include
6 | #include
7 |
8 | #include
9 | #include
10 |
11 | #include
12 | #include
13 | #include
14 | #include
15 | #include
16 | #include
17 |
18 | static const boost::filesystem::path dataDirPath = boost::filesystem::current_path().parent_path() / "data";
19 | static const boost::filesystem::path modelDirPath = boost::filesystem::current_path().parent_path() / "models";
20 |
21 | const char *USAGE_MESSAGE = "Usage: %s "
22 | "-s sequenceMap "
23 | "-m modelConfigFile\n";
24 | const char *OPEN_FILE_MESSAGE = "Could not open file %s\n";
25 | const char *OPEN_DIR_MESSAGE = "Could not open directory %s\n";
26 | const char *FILE_EXISTS_MESSAGE = "Output file %s already exists; don't overwrite\n";
27 |
28 | std::pair, int> detect(const std::shared_ptr &detector,
29 | const boost::filesystem::path &sequencePath,
30 | const std::string &modelType) {
31 | typedef std::chrono::duration msduration;
32 |
33 | // Make sure input directory exists
34 | boost::filesystem::path inputDirPath = dataDirPath / sequencePath / "images";
35 | if (!boost::filesystem::is_directory(inputDirPath)) {
36 | fprintf(stderr, OPEN_DIR_MESSAGE, sequencePath.c_str());
37 | exit(EXIT_FAILURE);
38 | }
39 |
40 | // Create output directory if not exists
41 | boost::filesystem::path outputDirPath = dataDirPath / sequencePath / modelType;
42 | if (!boost::filesystem::is_directory(outputDirPath)) {
43 | boost::filesystem::create_directories(outputDirPath);
44 | }
45 |
46 | // Make sure output file does not exist
47 | boost::filesystem::path outputPath = outputDirPath / "det.txt";
48 | if (boost::filesystem::exists(outputPath)) {
49 | fprintf(stderr, FILE_EXISTS_MESSAGE, outputPath.c_str());
50 | return std::pair(msduration(0), 0);
51 | }
52 |
53 | // Make sure output file can be opened
54 | std::ofstream outputStream;
55 | outputStream.open(outputPath.string());
56 | if (!outputStream.is_open()) {
57 | fprintf(stderr, OPEN_FILE_MESSAGE, outputPath.c_str());
58 | exit(EXIT_FAILURE);
59 | }
60 |
61 | std::vector imagePaths;
62 | std::copy(boost::filesystem::directory_iterator(inputDirPath),
63 | boost::filesystem::directory_iterator(),
64 | std::back_inserter(imagePaths));
65 | std::sort(imagePaths.begin(), imagePaths.end());
66 |
67 | msduration cumulativeDuration = std::chrono::milliseconds::zero();
68 | int frameCount = 0;
69 | for (auto imageIt = imagePaths.begin(); imageIt != imagePaths.end(); ++imageIt) {
70 | cv::Mat image = cv::imread(imageIt->string(), 1);
71 |
72 | auto startTime = std::chrono::high_resolution_clock::now();
73 | std::vector detections = detector->detect(image);
74 | auto endTime = std::chrono::high_resolution_clock::now();
75 |
76 | cumulativeDuration += std::chrono::duration_cast(
77 | endTime - startTime);
78 |
79 | for (auto detectionIt = detections.begin(); detectionIt != detections.end(); ++detectionIt) {
80 | outputStream << frameCount << ","
81 | << "-1" << "," // ID
82 | << detectionIt->bb.x1() << ","
83 | << detectionIt->bb.y1() << ","
84 | << detectionIt->bb.width << ","
85 | << detectionIt->bb.height << ","
86 | << detectionIt->confidence << ","
87 | << "-1,-1,-1" << "," // Unused
88 | << detectionIt->label << "\n";
89 | }
90 | ++frameCount;
91 | if (frameCount % 100 == 0) {
92 | std::cout << "Processed " << frameCount << " images" << std::endl;
93 | }
94 | }
95 | outputStream.close();
96 | return std::pair(cumulativeDuration, frameCount);
97 | }
98 |
99 | #ifdef USE_CAFFE
100 |
101 | int main(int argc, char **argv) {
102 |
103 | std::string sequenceMapName;
104 | std::string modelConfigFileName;
105 | std::string modelType;
106 | std::shared_ptr detector;
107 |
108 | int opt;
109 | while ((opt = getopt(argc, argv, "s:m:")) != -1) {
110 | switch (opt) {
111 | case 's':
112 | sequenceMapName = optarg;
113 | break;
114 | case 'm':
115 | modelConfigFileName = optarg;
116 | break;
117 | default:
118 | fprintf(stderr, USAGE_MESSAGE, argv[0]);
119 | exit(EXIT_FAILURE);
120 | }
121 | }
122 | if (sequenceMapName == "" || modelConfigFileName == "") {
123 | fprintf(stderr, USAGE_MESSAGE, argv[0]);
124 | exit(EXIT_FAILURE);
125 | }
126 |
127 | boost::filesystem::path modelConfigFilePath = modelDirPath / "config" / modelConfigFileName;
128 | std::ifstream modelConfigFile(modelConfigFilePath.string());
129 | if (modelConfigFile.is_open()) {
130 | std::string modelFile;
131 | std::string weightsFile;
132 | std::string meanValues;
133 | std::getline(modelConfigFile, modelType);
134 | std::getline(modelConfigFile, modelFile);
135 | std::getline(modelConfigFile, weightsFile);
136 | std::getline(modelConfigFile, meanValues);
137 | boost::filesystem::path modelFilePath = modelDirPath / modelFile;
138 | boost::filesystem::path weightsFilePath = modelDirPath / weightsFile;
139 | detector = std::make_shared(modelFilePath.string(), weightsFilePath.string(), meanValues);
140 | } else {
141 | fprintf(stderr, OPEN_FILE_MESSAGE, modelConfigFilePath.c_str());
142 | exit(EXIT_FAILURE);
143 | }
144 |
145 | boost::filesystem::path sequenceMapPath = dataDirPath / "seqmaps" / sequenceMapName;
146 | std::ifstream sequenceMap(sequenceMapPath.string());
147 | if (sequenceMap.is_open()) {
148 |
149 | std::chrono::duration cumulativeDuration;
150 | int cumulativeFrameCount = 0;
151 |
152 | std::string sequencePathString;
153 | while (std::getline(sequenceMap, sequencePathString)) {
154 | std::cout << "Sequence: " << sequencePathString << std::endl;
155 | auto durationFrameCount = detect(detector, sequencePathString, modelType);
156 | auto duration = std::chrono::duration_cast(durationFrameCount.first).count();
157 | std::cout << "Duration: " << duration << "ms"
158 | << " (" << double(durationFrameCount.second * 1000) / duration << "fps)\n";
159 | cumulativeDuration += durationFrameCount.first;
160 | cumulativeFrameCount += durationFrameCount.second;
161 | }
162 | sequenceMap.close();
163 | auto totalDuration = std::chrono::duration_cast(cumulativeDuration).count();
164 | std::cout << "Total duration: " << double(totalDuration) / 1000 << "s"
165 | << " (" << double(cumulativeFrameCount * 1000) / totalDuration << "fps)\n";
166 | } else {
167 | fprintf(stderr, OPEN_FILE_MESSAGE, sequenceMapName.c_str());
168 | exit(EXIT_FAILURE);
169 | }
170 | exit(EXIT_SUCCESS);
171 | }
172 |
173 | #else //USE_CAFFE
174 | int main(int argc, char **argv) {
175 | std::cerr << "This example requires Caffe; compile with USE_CAFFE.\n";
176 | exit(EXIT_FAILURE);
177 | }
178 | #endif //USE_CAFFE
--------------------------------------------------------------------------------
/cpp/src/examples/TrackDemo.cpp:
--------------------------------------------------------------------------------
1 | #include "../tracker/Tracker.h"
2 | #include "../tracker/PAOT.h"
3 | #include "../util/DetectionFileParser.h"
4 |
5 | #include
6 |
7 | #include
8 | #include
9 | #include
10 | #include
11 | #include
12 |
13 | const boost::filesystem::path dataDirPath = boost::filesystem::current_path().parent_path() / "data";
14 |
15 | const char *USAGE_MESSAGE = "Usage: %s "
16 | "-s sequenceMap "
17 | "-m modelType "
18 | "-f detectionFormat "
19 | "[-i frameInterval (default 1)] "
20 | "[-x (overwrites result)]\n";
21 | const char *OPEN_FILE_MESSAGE = "Could not open file %s\n";
22 | const char *FILE_EXISTS_MESSAGE = "Output file %s already exists; won't overwrite\n";
23 |
24 | std::pair, int> track(const boost::filesystem::path &sequencePath,
25 | const std::string &modelType,
26 | const std::string &detectionFormat,
27 | const int frameInterval,
28 | const bool doOverwriteResult) {
29 | typedef std::chrono::duration msduration;
30 |
31 | // Make sure input file exists
32 | boost::filesystem::path inputPath = dataDirPath / sequencePath / modelType / "det.txt";
33 | std::ifstream inputStream(inputPath.string());
34 | if (!inputStream.is_open()) {
35 | fprintf(stderr, OPEN_FILE_MESSAGE, inputPath.c_str());
36 | return std::pair(msduration(0), 0);
37 | }
38 |
39 | // Create output directory if not exists
40 | boost::filesystem::path outputDirPath = dataDirPath / "results" / sequencePath.parent_path() / modelType;
41 | if (!boost::filesystem::is_directory(outputDirPath)) {
42 | boost::filesystem::create_directories(outputDirPath);
43 | }
44 |
45 | // Make sure output file does not exist
46 | boost::filesystem::path outputPath = outputDirPath / (sequencePath.filename().string() + ".txt");
47 | if (boost::filesystem::exists(outputPath) && !doOverwriteResult) {
48 | fprintf(stderr, FILE_EXISTS_MESSAGE, outputPath.c_str());
49 | return std::pair(msduration(0), 0);
50 | }
51 |
52 | // Make sure output file can be opened
53 | std::ofstream outputStream;
54 | outputStream.open(outputPath.string());
55 | if (!outputStream.is_open()) {
56 | fprintf(stderr, OPEN_FILE_MESSAGE, outputPath.c_str());
57 | return std::pair(msduration(0), 0);
58 | }
59 |
60 | PAOT tracker;
61 |
62 | std::map> (*parseFileFunc)(std::ifstream &file);
63 | if (detectionFormat == "okutama") {
64 | parseFileFunc = DetectionFileParser::parseOkutamaFile;
65 | } else if (detectionFormat == "mot") {
66 | parseFileFunc = DetectionFileParser::parseMOTFile;
67 | } else {
68 | throw std::invalid_argument(detectionFormat + " not a valid detectionFormat");
69 | }
70 | const auto frameToDetections = parseFileFunc(inputStream);
71 |
72 | msduration cumulativeDuration = std::chrono::milliseconds::zero();
73 | int frameCount = 0;
74 | for (int frame = 0; frame < frameToDetections.rbegin()->first; ++frame) {
75 | if (frame % frameInterval == 0 && frameToDetections.find(frame) != frameToDetections.end()) {
76 | auto startTime = std::chrono::high_resolution_clock::now();
77 | std::vector trackings = tracker.track(frameToDetections.at(frame));
78 | auto endTime = std::chrono::high_resolution_clock::now();
79 |
80 | cumulativeDuration += std::chrono::duration_cast(
81 | endTime - startTime);
82 |
83 | for (auto trackingIt = trackings.begin(); trackingIt != trackings.end(); ++trackingIt) {
84 | outputStream << frame << ","
85 | << trackingIt->ID << ","
86 | << trackingIt->bb.x1() << ","
87 | << trackingIt->bb.y1() << ","
88 | << trackingIt->bb.width << ","
89 | << trackingIt->bb.height << ","
90 | << "1" << "," // Confidence
91 | << "-1,-1,-1" << "," // Unused
92 | << trackingIt->label << "\n";
93 | }
94 | ++frameCount;
95 | }
96 | }
97 | outputStream.close();
98 | return std::pair(cumulativeDuration, frameCount);
99 | }
100 |
101 | int main(int argc, char **argv) {
102 |
103 | std::string sequenceMapName;
104 | std::string modelType;
105 | std::string detectionFormat;
106 | int frameInterval = 1;
107 | bool doOverwriteResult = false;
108 |
109 | int opt;
110 | while ((opt = getopt(argc, argv, "s:m:f:i:x")) != -1) {
111 | switch (opt) {
112 | case 's':
113 | sequenceMapName = optarg;
114 | break;
115 | case 'm':
116 | modelType = optarg;
117 | break;
118 | case 'f':
119 | detectionFormat = optarg;
120 | break;
121 | case 'i':
122 | frameInterval = atoi(optarg);
123 | break;
124 | case 'x':
125 | doOverwriteResult = true;
126 | break;
127 | default:
128 | fprintf(stderr, USAGE_MESSAGE, argv[0]);
129 | exit(EXIT_FAILURE);
130 | }
131 | }
132 |
133 | if (sequenceMapName == "" || modelType == "" || detectionFormat == "") {
134 | fprintf(stderr, USAGE_MESSAGE, argv[0]);
135 | exit(EXIT_FAILURE);
136 | }
137 | if (frameInterval < 1) {
138 | fprintf(stderr, "frameInterval must be a positive integer");
139 | exit(EXIT_FAILURE);
140 | }
141 |
142 | boost::filesystem::path sequenceMapPath = dataDirPath / "seqmaps" / sequenceMapName;
143 | std::ifstream sequenceMap(sequenceMapPath.string());
144 | if (sequenceMap.is_open()) {
145 |
146 | std::chrono::duration cumulativeDuration;
147 | int cumulativeFrameCount = 0;
148 |
149 | std::string sequencePathString;
150 | while (getline(sequenceMap, sequencePathString)) {
151 | std::cout << "Sequence: " << sequencePathString << std::endl;
152 | auto durationFrameCount = track(sequencePathString, modelType, detectionFormat, frameInterval,
153 | doOverwriteResult);
154 | auto duration = std::chrono::duration_cast(durationFrameCount.first).count();
155 | std::cout << "Duration: " << duration << "ms"
156 | << " (" << double(durationFrameCount.second * 1000) / duration << "fps)\n";
157 | cumulativeDuration += durationFrameCount.first;
158 | cumulativeFrameCount += durationFrameCount.second;
159 | }
160 | sequenceMap.close();
161 | auto totalDuration = std::chrono::duration_cast(cumulativeDuration).count();
162 | std::cout << "Total duration: " << double(totalDuration) / 1000 << "s"
163 | << " (" << double(cumulativeFrameCount * 1000) / totalDuration << "fps)\n";
164 | } else {
165 | fprintf(stderr, OPEN_FILE_MESSAGE, sequenceMapName.c_str());
166 | exit(EXIT_FAILURE);
167 | }
168 | exit(EXIT_SUCCESS);
169 | }
--------------------------------------------------------------------------------
/cpp/src/tracker/Affinity.cpp:
--------------------------------------------------------------------------------
1 | #include "Affinity.h"
2 |
3 | #include
4 |
5 | double Affinity::euclDist(const BoundingBox &a, const BoundingBox &b) {
6 | return std::sqrt(std::pow(a.cx - b.cx, 2) + std::pow(a.cy - b.cy, 2));
7 | }
8 |
9 | double Affinity::iou(const BoundingBox &a, const BoundingBox &b) {
10 | double xx1 = std::max(a.x1(), b.x1());
11 | double yy1 = std::max(a.y1(), b.y1());
12 | double xx2 = std::min(a.x2(), b.x2());
13 | double yy2 = std::min(a.y2(), b.y2());
14 | double width = std::max(xx2 - xx1, 0.);
15 | double height = std::max(yy2 - yy1, 0.);
16 | double intersection = width * height;
17 | double uni = a.area() + b.area() - intersection;
18 | return intersection / uni;
19 | }
20 |
21 | double Affinity::linCost(const BoundingBox &a, const BoundingBox &b) {
22 | double positionCost = std::sqrt(std::pow(a.cx - b.cx, 2) + std::pow(a.cy - b.cy, 2));
23 | double shapeCost = std::sqrt(std::pow(a.width - b.width, 2) + std::pow(a.height - b.height, 2));
24 | return positionCost * shapeCost;
25 | }
26 |
27 | double Affinity::expCost(const BoundingBox &a, const BoundingBox &b) {
28 | // It is expected that a is detection and b is prediction
29 | double positionWeight = 0.5;
30 | double shapeWeight = 1.5;
31 | double positionCost = std::exp(-positionWeight * (
32 | std::pow((a.cx - b.cx) / a.width, 2) +
33 | std::pow((a.cy - b.cy) / a.height, 2)));
34 | double shapeCost = std::exp(-shapeWeight * (
35 | std::abs(a.width - b.width) / (a.width + b.width) +
36 | std::abs(a.height - b.height) / (a.height + b.height)));
37 | return positionCost * shapeCost;
38 | }
--------------------------------------------------------------------------------
/cpp/src/tracker/Affinity.h:
--------------------------------------------------------------------------------
1 | #ifndef CPP_AFFINITY_H
2 | #define CPP_AFFINITY_H
3 |
4 |
5 | #include "../util/BoundingBox.h"
6 |
7 | class Affinity {
8 | public:
9 | /**
10 | * Euclidian distance
11 | * Small value indicates similarity
12 | */
13 | static double euclDist(const BoundingBox &a, const BoundingBox &b);
14 |
15 | /**
16 | * Intersection over union
17 | * Large value indicates similarity
18 | * From: Simple Online and Realtime Tracking
19 | * (Alex Bewley, Zongyuan Ge, Lionel Ott, Fabio Ramos, Ben Upcroft)
20 | */
21 | static double iou(const BoundingBox &a, const BoundingBox &b);
22 |
23 | /**
24 | * Combination of linear similarity in position and shape
25 | * Small value indicates similarity
26 | * From: Online multi-target tracking with strong and weak detections
27 | * (Ricardo Sanchez-Matilla, Fabio Poiesi, Andrea Cavallaro Centre)
28 | */
29 | static double linCost(const BoundingBox &a, const BoundingBox &b);
30 |
31 | /**
32 | * Combination of exponential similarity in position and shape
33 | * Large value indicates similarity
34 | * From: POI: Multiple Object Tracking with High Performance Detection and Appearance Feature
35 | * (Fengwei Yu, Wenbo Li, Quanquan Li, Yu Liu, Xiaohua Shi, Junjie Yan)
36 | * @param a BoundingBox from Detection
37 | * @param b BoundingBox from Predictor
38 | */
39 | static double expCost(const BoundingBox &a, const BoundingBox &b);
40 |
41 | private:
42 | // Prevent instantiation
43 | Affinity() {};
44 | };
45 |
46 |
47 | #endif //CPP_AFFINITY_H
--------------------------------------------------------------------------------
/cpp/src/tracker/PAOT.cpp:
--------------------------------------------------------------------------------
1 | #include "PAOT.h"
2 |
3 | #include "Affinity.h"
4 | #include "predictor/kalman/KalmanPredictor.h"
5 | #include "predictor/particle/ParticlePredictor.h"
6 |
7 | #include
8 |
9 | // Methods
10 |
11 | std::vector PAOT::track(const std::vector &detections) {
12 | frameCount++;
13 |
14 | // Filter detections on confidence
15 | std::vector strongDetections;
16 | for (const auto &detection : detections) {
17 | if (detection.confidence > detectionThreshold) {
18 | strongDetections.push_back(detection);
19 | }
20 | }
21 |
22 | Association association = associateDetectionsToPredictors(strongDetections, predictors,
23 | Affinity::expCost, affinityThreshold);
24 |
25 | // Update matched predictors with assigned detections
26 |
27 | for (const auto &match : association.matching) {
28 | predictors.at(match.second)->update(strongDetections.at(match.first));
29 | }
30 |
31 | for (const auto p : association.unmatchedPredictors) {
32 | predictors.at(p)->update();
33 | }
34 |
35 | // Create and initialise new predictors for unmatched detections
36 | for (const auto id : association.unmatchedDetections) {
37 | auto predictor = std::make_shared(strongDetections.at(id), ++trackCount);
38 | predictors.push_back(predictor);
39 | }
40 |
41 | // Remove predictors that have been inactive for too long
42 | predictors.erase(std::remove_if(
43 | predictors.begin(), predictors.end(),
44 | [this](const std::shared_ptr &predictor) {
45 | return predictor->getTimeSinceUpdate() > maxAge;
46 | }), predictors.end());
47 |
48 | // Return trackings from active predictors
49 | std::vector trackings;
50 | for (auto it = predictors.begin(); it != predictors.end(); ++it) {
51 | if ((*it)->getTimeSinceUpdate() < 1 &&
52 | ((*it)->getHitStreak() >= minHits || frameCount <= minHits)) {
53 | trackings.push_back((*it)->getTracking());
54 | }
55 | }
56 | return trackings;
57 | }
58 |
59 | PAOT::Association PAOT::associateDetectionsToPredictors(
60 | const std::vector &detections,
61 | const std::vector> &predictors,
62 | double (*affinityMeasure)(const BoundingBox &a, const BoundingBox &b),
63 | double affinityThreshold) {
64 |
65 | const int DOUBLE_PRECISION = 100;
66 | std::vector> matches;
67 | std::vector unmatchedDetections;
68 | std::vector unmatchedPredictors;
69 |
70 | if (predictors.empty()) {
71 | for (int i = 0; i < detections.size(); ++i)
72 | unmatchedDetections.push_back(i);
73 | return PAOT::Association{matches, unmatchedDetections, unmatchedPredictors};
74 | }
75 |
76 | dlib::matrix cost(detections.size(), predictors.size());
77 | for (size_t row = 0; row < detections.size(); ++row) {
78 | for (size_t col = 0; col < predictors.size(); ++col) {
79 | cost(row, col) = int(DOUBLE_PRECISION * affinityMeasure(
80 | detections.at(row).bb,
81 | predictors.at(col)->getPredictedNextDetection().bb));
82 | }
83 | }
84 |
85 | // Zero-pad to make it square
86 | if (cost.nr() > cost.nc()) {
87 | cost = dlib::join_rows(cost, dlib::zeros_matrix(1, cost.nr() - cost.nc()));
88 | } else if (cost.nc() > cost.nr()) {
89 | cost = dlib::join_cols(cost, dlib::zeros_matrix(cost.nc() - cost.nr(), 1));
90 | }
91 |
92 | std::vector assignment = dlib::max_cost_assignment(cost);
93 |
94 | // Filter out matches with low IoU, including those for indices from padding
95 | for (int d = 0; d < assignment.size(); ++d) {
96 | if (cost(d, assignment[d]) < affinityThreshold * DOUBLE_PRECISION) {
97 | if (d < detections.size()) {
98 | unmatchedDetections.push_back(d);
99 | }
100 | if (assignment[d] < predictors.size()) {
101 | unmatchedPredictors.push_back(int(assignment[d]));
102 | }
103 | } else {
104 | matches.push_back(std::pair(d, assignment[d]));
105 | }
106 | }
107 | return PAOT::Association{matches, unmatchedDetections, unmatchedPredictors};
108 | }
--------------------------------------------------------------------------------
/cpp/src/tracker/PAOT.h:
--------------------------------------------------------------------------------
1 | #ifndef CPP_PAOT_H
2 | #define CPP_PAOT_H
3 |
4 |
5 | #include "Tracker.h"
6 | #include "predictor/Predictor.h"
7 | #include "predictor/kalman/KalmanPredictor.h"
8 |
9 | #include
10 | #include
11 |
12 | class PAOT : public Tracker {
13 | struct Association;
14 |
15 | public:
16 | PAOT() = default;
17 |
18 | virtual ~PAOT() = default;
19 |
20 | /**
21 | * Uses a linear velocity Kalman filters to predict locations of objects from previous frame.
22 | * Associates detections to Kalman filters using an Affinity measure and the Hungarian Algorithm.
23 | */
24 | std::vector track(const std::vector &detections) override;
25 |
26 | private:
27 | const int maxAge = 2; // Original: 1
28 | const int minHits = 0; // Original: 3
29 | const double detectionThreshold = 0.4;
30 | const double affinityThreshold = 0.1;
31 | std::vector> predictors;
32 | int trackCount = 0;
33 | int frameCount = 0;
34 |
35 | /**
36 | * Uses an Affinity measure and Hungarian algorithm to determine which detection corresponds to which Kalman filter.
37 | */
38 | static Association associateDetectionsToPredictors(
39 | const std::vector &detections,
40 | const std::vector> &predictors,
41 | double (*affinityMeasure)(const BoundingBox &a, const BoundingBox &b),
42 | double affinityThreshold);
43 |
44 | struct Association {
45 | std::vector> matching;
46 | std::vector unmatchedDetections;
47 | std::vector unmatchedPredictors;
48 | };
49 | };
50 |
51 |
52 | #endif //CPP_MCSORT_H
--------------------------------------------------------------------------------
/cpp/src/tracker/RandomTracker.cpp:
--------------------------------------------------------------------------------
1 | #include "RandomTracker.h"
2 |
3 | #include