# HOG-Pedestrian-Detector
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This repository contains the code for a MATLAB implementation of a basic HOG + SVM pedestrian detector form my Computer Science Master [thesis](https://upcommons.upc.edu/bitstream/handle/2099.1/21343/95066.pdf?sequence=1&isAllowed=y)
## Disclaimer
If you are going to use this code, please read the `LICENCE` and keep in mind that I `PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY
OF ANY KIND`.
I partially adapted this code-base to newer versions of MATLAB but is very likely you find discrepancies in how some MATLAB functions work.
I am in general happy to help understanding the project if you ask nicely but since the implementation of the project is now several years old and MATLAB has evolved, some functions might behave differently and I won't be updating the project continuously nor answering about how to update the code to newer MATLAB versions.
## Requirements
* MATLAB >= R2017b
* [libsvm](https://github.com/cjlin1/libsvm/tree/v322) >= 3.22
## Installation
Please refer to MATLAB and libsvm documentation to install.
## Data
## Run
The project was developed on a Windows machine and now being resurrected on a Linux one, so you should be good in any platform as long as you can run MATLAB.
### Setting the environment
1. Add the `libs` directory and **all** sub-directories to MATLABs path.
Either through the [command window](https://www.mathworks.com/help/matlab/ref/addpath.html) or through the GUI.
2. Make sure `libsvm` is visible to MATLAB. If you are not sure if your installation of `libsvm` went alright, you can check with:
```matlab
which -all svmtrain
```
Which should show something like:
```
~/HOG-Pedestrian-Detector/libs/libsvm-3.22/matlab/svmtrain.mexa64
/usr/local/MATLAB/R2017b/toolbox/stats/stats/svmtrain.m % Shadowed
```
There are several entry points to the project, but here the two main ones are shown:
### Train
Assuming there's a `models` directory where trained models will be saved and that the positive and negative images can be found in `dataset/Test/pos` and `dataset/Test/neg` respectively.
Train an SVM model named `test`
```matlab
model = train_svm("test", ["./models", "dataset/Train/pos" "dataset/Train/neg"]);
```
### Eval
To evaluate the just trained model:
```matlab
test_svm(model.test, ["dataset/Test/pos" "dataset/Test/neg"]);
```
Note `test_svm` expects `model.<model-given-name-to-train-function>`...
### PCA versions of train / test
```matlab
[model, Ureduce] = train_svm_PCA("test_pca", ["./models", "dataset/Train/pos" "dataset/Train/neg"]);
test_svm_PCA(model.test_pca, Ureduce, ["dataset/Test/pos", "dataset/Test/neg"]);
```
## Known issues & contributions
Old MATLAB version used to concatenate strings by enclosing them between squared brackets but doesn't look like valid any longer. In that case you should use the `strcat` function. For example when constructing paths, so:
```matlab
path = ['folder', 'filename', '.extension'] % this is wrong!
path = strcat('folder', 'filename', '.extension') % this is right!
```
If you enjoyed this repository and find things that are not working any longer, you are very welcome to open a PR with fixes and I'll happily introduce them.
## License
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没有合适的资源?快使用搜索试试~ 我知道了~
HOG行人检测器:基本HOG + SVM行人检测器的MATLAB实现
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共386个文件
png:154个
m:68个
txt:39个
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温馨提示
HOG行人检测器 该存储库包含我的计算机科学硕士基本HOG + SVM行人检测器的MATLAB实现的代码 免责声明 如果要使用此代码,请阅读LICENCE并记住,我按PROVIDE THE PROGRAM "AS IS" WITHOUT WARRANTY OF ANY KIND 。 我对该代码库进行了部分调整,以使其适应最新版本的MATLAB,但您很可能会发现某些MATLAB函数的工作方式存在差异。 总的来说,如果您问得很好,我很乐于帮助您理解该项目,但是由于该项目的实施已有数年之久并且MATLAB已经发展,因此某些功能的行为可能会有所不同,因此我将不会持续更新该项目,也不会回答有关如何将
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