Abstract：这个部分用于使用传统图像特征的方法，基于滑动窗口的的目标检测
模块，包含Config模块，FeatureExtractor模块，和Classifier模块，下面将简单
介绍使用方法和各模块的功能。
python main.py --action train
python main.py --action test
| Config |
FeatureExtractor |
Classifier |
| 定义project的各种参量，包括使用的feature类型，project_id，路径（训练集/ |
|
|
| 测试集/模型）以及各种feature提取的参数 |
定义特征提取函数，该模块包含通用的 |
|
| 图像处理函数，以及特定的feature提取函数 |
定义分类器的训练以及预测函数 |
|
| Param |
Definition |
| DES_TYPE |
The feature extraction type |
| CLF_TYPE |
The classifier model(eg.SVM,MLP) |
| project_id |
Self_defined project name |
| THRESHOLD |
The threshold when applying nms() |
| DOWNSCALE |
The downscale when applying pyramid_gaussian() |
| MIN_WDW_SIZE |
The min size of windows detected |
| STEP_SIZE |
The slide step when sliding across the image |
FeatureExtractor
| Function |
Definition |
| resize_crop_by_short() |
Resize and crop the input image, output image shape(short_len, short_len) |
| resize_by_short() |
Resize the image |
| image_preprocess_size() |
Resize and crop all training images |
| sliding_window() |
Slide window at a fix window size |
| overlapping_area() |
Calculate the overlap area of two detections |
| nms() |
Apply NMS |
| process_image() |
Extract features from input image |
| extract_features() |
Extract features of all input images |
| Function |
Definition |
| load_data() |
Load all features of images |
| train_classifier() |
Train the model |
| load_model() |
Load the model |
| predict() |
Predict the class or score of the input image |
| test_classifier() |
Test classifier on the test images |