# toolbox

**Repository Path**: automlresearch/toolbox

## Basic Information

- **Project Name**: toolbox
- **Description**: various tools  such as label-tools , data-augmentation  , etc.
- **Primary Language**: Unknown
- **License**: Not specified
- **Default Branch**: master
- **Homepage**: None
- **GVP Project**: No

## Statistics

- **Stars**: 0
- **Forks**: 0
- **Created**: 2020-08-30
- **Last Updated**: 2020-12-19

## Categories & Tags

**Categories**: Uncategorized

**Tags**: None

## README

# toolbox
All kinds of utils for format convertion or something else (described in readme files)</br>
Each python file matches some samples inside.</br>
More details are marked in the python files as **annotation** or **`README.md` file** inside the folder.</br>


## converter 
Some conversion files included here,I'll update it if necessary.</br>
* **txt2voc**</br>
The tool inside helps you to conver txt in certain format to voc format.  
Provided txt labels ground truth in form of `NWPU VHR-10` , it's not a hard job to change related code for your owm labels.  
NWPU VHR-10's label is showed as follow:  
```
2,(270,296),(358,685)
2,(366,278),(453,661)
4,(541,633),(727,698)
```

* **voc2txt**  
User-friendly work for extracting imformation from xml files. And an example is attached for better understanding.  

* **labelme2coco**  
It's a bit hard to finish this work , cause the widespread wrong version about it , I hate plagiarism :)  
This tool helps you to convert json file created by labelme to COCO style for training.     
**Attentions:**   
    1.If you want to label the segmentation mask , there is `no need` to label bbox!(Or bugs arised)   
    2.When using labelme , pls named mask according to COCO format,such as `vehicle_car_1`.(supercategory,category,instance id)    

* **voc2coco**    
  
* **xml2yolo**    
Yolo format: class_id + Normalized xywh (id markded from 0) for each row.  
Supported xml style: **VOC**, **HRSC**(8 points & rotated)

* **icdar2yolo**   
For challenge 4, trans polygon to rbox in yolo format.(btw, challenge1 labeled w.o rotation!)  

* **icdar2voc**  
trans from IC15 to VOC format.



## dataset  
* **dataset_partition**  
Dataset partition for train, val, test part.  
**mark**: `x2` means train + val, `x3` means train + val + test.  
Remember to enlarge val & test set if your dataset is tiny. (such as 6:2:2)   

* **subdataset_generation**    
Division of subset from total dataset, used for hyperparameter adjust.  
(you can regard it as `x1` dataset_partition)  

* **generate_imageset**    
Generate trainval setting files.    
(Two mode included:yolo and voc)    

* **operate_on_datasets**    
Operations on dataset , such as copy, label matching.     


## data augmentation  
* **augmentation**   
Various kinds of data augmentation implementions as well as some demos are concluded inside .  
* **img_aug**  
Strongly recommended! Various tools for augmentation and easy to get started.  


## drawbox
* **drawbox**  
Useful tool for drawing bbox through providied points.The only customed part is your points obtaining function. 

## mAP
Support rbox evaluation and mAP calculation for object detection.

## matplotlib
Provided a template for plotting 2D and 3D figure.


## log_show
Visualization for training log files.


## Spider
Easy implemention for crawling info from website.


## other tools
* **img_format_trans**    
A simple tool for conversion of image format.  

* **visdom-train-example**  
A example for training while monitoring on loss and ac curve.More details and attention have been attached to file inside. 

* **python-cmd**  
Linux command execution through python file , provided as a easy but sufficient demo.  
Beside,`exec` commond also helps for many cases ,take good use of it.(such as [drawing pictures](https://github.com/ming71/toolbox/blob/b473ea001c2498fe927115d0c4a66d1cd4e30a7f/matplotlib/HuMonent.py#L172))  


* **crop_bbox_and_save**   
Crop bbox area from raw image and save for other usage.


 * **K-means**   
K-means  implement for box clustering.

* **skewiou**  
For skewiou calc.

* **zip**  
zip and unzip files.