https://github.com/kleinyuan/doppia
Github version of rodrigob/doppia with some fixes and documentations
https://github.com/kleinyuan/doppia
computer-vision doppia ground-estimation object-detection
Last synced: about 1 year ago
JSON representation
Github version of rodrigob/doppia with some fixes and documentations
- Host: GitHub
- URL: https://github.com/kleinyuan/doppia
- Owner: KleinYuan
- License: other
- Created: 2017-09-10T13:55:06.000Z (over 8 years ago)
- Default Branch: master
- Last Pushed: 2017-09-11T08:49:20.000Z (over 8 years ago)
- Last Synced: 2025-03-26T05:33:14.110Z (about 1 year ago)
- Topics: computer-vision, doppia, ground-estimation, object-detection
- Language: C++
- Homepage:
- Size: 20.9 MB
- Stars: 6
- Watchers: 2
- Forks: 2
- Open Issues: 0
-
Metadata Files:
- Readme: README.md
- License: license.text
Awesome Lists containing this project
README
# Intro
Doppia is a collection of several research publications and original [repo](https://bitbucket.org/rodrigob/doppia) is hosted on bitbucket.
# Docker Run
Well, if you are too lazy to read this whole readme, going through all the deatils of setting up the machine, compile the C++ applications and run demo with various flags, fine, I made a docker version for you to just execute 2 lines of code doing everything for you:
```
# First of all, git clone this repo and in here we assume, you navigated to the root of this repo
# Then, just simply build the docker image by running
make build
# Then, it will take a while and build a docker image at around 8 GB, thanks for opencv, then you just simply run it
make run
```
And then, it will spin up a container with ground_estimation app compiled. You can run the demo by:
```
./ground_estimation -c test.config.ini --gui.disable true
```
Then you are supposed to see logs below:
```
Ground estimation. Rodrigo Benenson @ KULeuven. 2010-2011.
Parsed the configuration file test.config.ini
Creating new log file stixel_world.out.txt
Using stereo camera calibration file: ../../video_input/calibration/stereo_calibration_bahnhof.proto.txt
2017-09-11 08:46:07 {7f388f16f800} [ StereoCameraCalibration ] : stereo_calibration_data name: Andreas Ess Bahnhofstrasse sequence stereo calibration
Reading files:
../../../data/sample_test_images/bahnhof/image_00000000_0.png
../../../data/sample_test_images/bahnhof/image_00000000_1.png
Average iteration speed 39.3800 [Hz] (in the last 10 iterations)
Requested frame number 11 but frames should be in range (0, 10)
Processed a total of 10 input frames
End of game, have a nice day.
```
It means you are successfully running the demo.
If you wanna do more, then continue within this docker container and I strongly suggest you also read rest of the readme to get a better idea.
# Machine Setup
- [X] Ubuntu (preferred)
- [X] GPU hardware
- [X] CUDA with capacity to be higher than 2.0
- [X] All boost libraries
- [X] Google protocol buffer
- [X] OpenCV 2.4 (3.0 is not supported yet)
- [X] libjpeg, libpng
- [X] libSDL
- [X] CMAKE >= 2.4.3
Dependencies | Version | Installation |
--- | --- | ---
CUDA | 8.0 | Follow this [procedures](https://github.com/KleinYuan/easy-yolo#b-environment-gpu) |
OpenCV | 2.4.13 | Run this [script](https://github.com/KleinYuan/doppia/blob/master/dependencies/opencv_install.sh)
Protobuf | latest | Run this [script](https://github.com/KleinYuan/doppia/blob/master/dependencies/protobuf_install.sh)
All boost libraries | latest | `sudo apt-get install libboost-all-dev`
libjpeg | latest | `sudo apt-get install libjpeg-dev`
libpng | latest | `sudo apt-get install libpng-dev`
libSDL | latest | `sudo apt-get install libSDL-dev`
# Compile and Run Demo
The code includes many applications and they all locate under `src/applications`.
Before doing everything, you need to modify this [line](https://github.com/KleinYuan/doppia/blob/master/common_settings.cmake#L342) in `common_settings.cmake` to replace the placeholder with your machine name.
Then run following script to ensure the protocol buffer files match the version installed in your system.
```
generate_protocol_buffer_files.sh
```
### 0. Summary
Basically, this is a project based on C++, meaning, how it works is that you need to 1) compile the code and obtain an executable, 2) config parameters and run executable against input.
Therefore, we describe compile (ground_estimation/stixel_world as CPU only example and objects_detection as GPU example) first then how to run the demo.
### 1. Compile
#### 1.1 CPU Only Compile
Example for ground_estimation app
```
# Navigate to the path
cd doppia/src/applications/ground_estimation
# Compile
cmake -D CMAKE_BUILD_TYPE=RelWithDebInfo . && make -j2
```
Example for stixel_world
```
cd doppia/src/applications/stixel_world
cmake . && make -j2
```
#### 1.2 GPU Compile
objects_detection is build in a way to work with GPU
```
cd doppia/src/applications/objects_detection
cmake -D CMAKE_BUILD_TYPE=RelWithDebInfo -D USE_GPU=ON . && make -j2
```
### 2. Run Demo
#### 2.1 Run Ground Estimation Demos
```
./ground_estimation -c test.config.ini
```
#### 2.2 Run Stixel World Demos
```
# Demo 1
OMP_NUM_THREADS=4 ./stixel_world -c fast.config.ini --gui.disable false
```
```
# Demo 2
OMP_NUM_THREADS=4 ./stixel_world -c fast_uv.config.ini --gui.disable false
```
#### 2.3 Run Object Detection Demos
```
# Demo 1
OMP_NUM_THREADS=4 ./objects_detection -c cvpr2012_very_fast_over_bahnhof.config.ini --gui.disable false
```
```
# Demo 2
OMP_NUM_THREADS=4 ./objects_detection -c cvpr2012_inria_pedestrians.config.ini --gui.disable false
```
```
# Demo 3
OMP_NUM_THREADS=4 ./objects_detection -c cvpr2012_chnftrs_over_bahnhof.config.ini --gui.disable false
```
```
# Demo 4
./objects_detection -c eccv2014_face_detection_pascal.config.ini --gui.disable false
```
#### 2.4 Summary
So basically, after compile an app, you just need to define a config file with format like `*.config.ini` and use `objects_detection` executable to run against it.
For example, `pedestrians detection` has an example config [file](https://github.com/KleinYuan/doppia/blob/master/src/applications/objects_detection/cvpr2012_inria_pedestrians.config.ini) and in this file, you can define whether you wanna input from directory or camera, scales, stride, mask, ...etc. For the example config of pedestrians detection, the input is sourced from [directory](https://github.com/KleinYuan/doppia/tree/master/data/sample_test_images/inria), which you can also easily define your own ones.
For more details, you can run `./objects_detection --help` to see all the options.
For example, if you want to save the detections and save screenshots into local folder then you can use `--save_detections and --gui.save_all_screenshots` flags:
```
./objects_detection -c ***.ini --save_detection=1 --gui.disable=false --gui.save_all_screenshots=1
```
You can find the detailed info by running `./objects_detection --help`
### 3. Modifications
#### 3.1 OpenCV issues
Due to some OpenCV linking issues originally potentially from wrong order of linking lib, we have a fix for compiling apps by commenting out following in all `CMakeLists.txt`. (Original issue discussion can be found [here](https://bitbucket.org/rodrigob/doppia/issues/135/ground_estimation-linking-problems)).
```
#set(opencv_LIBRARIES
# opencv_core opencv_imgproc opencv_highgui opencv_ml
# opencv_video opencv_features2d
# opencv_calib3d
# opencv_objdetect opencv_contrib
# opencv_legacy opencv_flann
# opencv_gpu
# ) # quick hack for opencv2.4 support
```
Example changes:
Name | Line |
--- | ---
ground_estimation | [line_40](https://github.com/KleinYuan/doppia/blob/master/src/applications/ground_estimation/CMakeLists.txt#L40)
stixel_world | [line_40](https://github.com/KleinYuan/doppia/blob/master/src/applications/stixel_world/CMakeLists.txt#L40)
objects_detection | [line_42](https://github.com/KleinYuan/doppia/blob/master/src/applications/objects_detection/CMakeLists.txt#L42)
#### 3.2 CUDA modifications
You need to modify the cuda path with correct version on your machine and in here, the changes are below and original discussions can be found [here](https://bitbucket.org/rodrigob/doppia/issues/80/gpuveryfastintegralchannelsdetector):
- [X] Replacing all `cuda-5.5` with `cuda-8.0` since that's what I tested (you may have a different version and check by `ls /usr/local | grep cuda`)
- [X] Replacing all `cuda-5.5` in all related CMakeList.txt, for example in [objects_detection](https://github.com/KleinYuan/doppia/blob/master/src/applications/objects_detection/CMakeLists.txt#L78)
- [X] Adding `USE_GPU` flag in objects_detection [CMakeList.txt](https://github.com/KleinYuan/doppia/blob/master/src/applications/objects_detection/CMakeLists.txt#L32)
- [X] Indexing CUDA arch specifically in objects_detection [CMakeList.txt](https://github.com/KleinYuan/doppia/blob/master/src/applications/objects_detection/CMakeLists.txt#L59) and make sure that the arch is the one your host machine is compatible, otherwise you may still be able to compile but throw errors
- [X] Enforce objects_detection to be build with GPU ON by adding flag in cmake [command](https://github.com/KleinYuan/doppia#gpu-code)