# convert2Yolo **Repository Path**: hox/convert2Yolo ## Basic Information - **Project Name**: convert2Yolo - **Description**: https://github.com/ssaru/convert2Yolo.git - **Primary Language**: Unknown - **License**: Not specified - **Default Branch**: master - **Homepage**: None - **GVP Project**: No ## Statistics - **Stars**: 0 - **Forks**: 0 - **Created**: 2020-07-29 - **Last Updated**: 2020-12-19 ## Categories & Tags **Categories**: Uncategorized **Tags**: None ## README # Convert2Yolo Object Detection annotation Convert to [Yolo Darknet](https://pjreddie.com/darknet/yolo/) Format Support DataSet : 1. COCO 2. VOC 3. UDACITY Object Detection 4. KITTI 2D Object Detection ## Pre-Requiredment ``` pip3 install -r requirements.txt ``` ## Required Parameters each dataset requried some parameters see [example.py](https://github.com/ssaru/convert2Yolo/blob/master/example.py) 1. --datasets - like a COCO / VOC / UDACITY / KITTI ```bash --datasets COCO ``` 2. --img_path - it directory path. not file path ```bash --img_path ./example/kitti/images/ ``` 3. --label - it directory path. not file path (some datasets give label `*.json` or `*.csv` . this case use file path) ```bash --label ./example/kitti/labels/ ``` OR ```bash --label ./example/kitti/labels/label.json or --label ./example/kitti/labels/label.csv ``` 4. --convert_output_path - it directory path. not file path ```bash --convert_output_path ./ ``` 5. --img_type - like a `*.png`, `*.jpg` ```bash --img_type ".jpg" ``` 6. --manipast_path - it need train yolo model in [darknet framework](https://pjreddie.com/darknet/) ```bash --manipast_path ./ ``` 7. --cla_list_file(`*.names`) - it is `*.names` file contain class name. refer [darknet `*.name` file](https://github.com/pjreddie/darknet/blob/master/data/voc.names) ```bash --cls_list_file voc.names ``` ### *.names file example ``` aeroplane bicycle bird boat bottle bus car cat chair cow diningtable dog horse motorbike person pottedplant sheep sofa train tvmonitor ``` ## Example ### 1. example command ```bash python3 example.py --datasets [COCO/VOC/KITTI/UDACITY] --img_path --label --convert_output_path --img_type [".jpg" / ".png"] --manipast_path --cls_list_file <*.names file path> >> ex) python3 example.py --datasets KITTI --img_path ./example/kitti/images/ --label ./example/kitti/labels/ --convert_output_path ./ --img_type ".jpg" --manipast_path ./ --cls_list_file names.txt ``` ### 2. VOC datasets #### description of dataset directory suppose that VOC dataset location are `~/VOC` and VOC folder contains `VOCdevkit` folder here are structure for `VOCdevkit` **`VOCdevkit`** ```bash $ tree -L 2 . └── VOC2012 ├── Annotations ├── ImageSets ├── JPEGImages ├── SegmentationClass └── SegmentationObject ``` we use only `Annotations` and `JPEGImages` folder - Annotations : Object Detection label folder - JPEGImages : Image data **Annotations** ```bash $ tree -L 1 . ├── 2007_000027.xml ├── 2007_000032.xml ├── 2007_000033.xml ... ├── 2012_004319.xml ├── 2012_004326.xml ├── 2012_004328.xml ├── 2012_004329.xml ├── 2012_004330.xml └── 2012_004331.xml ``` **JPEGImages** ```bash . ├── 2007_000027.jpg ├── 2007_000032.jpg ├── 2007_000033.jpg ... ├── 2012_004328.jpg ├── 2012_004329.jpg ├── 2012_004330.jpg └── 2012_004331.jpg ``` #### make `*.names` file now make `*.names` file in `~/VOC/` refer [darknet `voc.names` file](https://github.com/pjreddie/darknet/blob/master/data/voc.names) ```bash aeroplane bicycle bird boat bottle bus car cat chair cow diningtable dog horse motorbike person pottedplant sheep sofa train tvmonitor ``` #### VOC datasets convert to YOLO format now execute example code. this example assign directory for saving `YOLO` label `~/YOLO/` and assign `manipast_path` is `./` **make YOLO folder** ```bash $ mkdir ~/YOLO ``` **VOC convert to YOLO** ```bash python3 example.py --datasets VOC --img_path ~/VOCdevkit/VOC2012/JPEGImages/ --label ~/VOCdevkit/VOC2012/Annotations/ --convert_output_path ~/YOLO/ --img_type ".jpg" --manipast_path ./ --cls_list_file ~/VOC/voc.names >> VOC Parsing: |████████████████████████████████████████| 100.0% (17125/17125) Complete YOLO Generating:|████████████████████████████████████████| 100.0% (17125/17125)Complete YOLO Saving: |████████████████████████████████████████| 100.0% (17125/17125) Complete ``` #### Result now check result files (`~/YOLO/`, `./manifast.txt`) **`~/YOLO/`** ```bash $ tree -L 1 >> ├── 2012_004326.txt ├── 2012_004328.txt ├── 2012_004329.txt ├── 2012_004330.txt └── 2012_004331.txt ... ├── 2012_004326.txt ├── 2012_004328.txt ├── 2012_004329.txt ├── 2012_004330.txt └── 2012_004331.txt ``` **`2012_004331.txt`** ```bash $ cat 2012_004331.txt >> 14 0.31 0.34 0.212 0.547 ``` **`./manifast.txt`** ```bash $ cat ./manifast.txt >> ~/VOC/VOCdevkit/VOC2012/JPEGImages/2010_000420.jpg ~/VOC/VOCdevkit/VOC2012/JPEGImages/2010_003674.jpg ~/VOC/VOCdevkit/VOC2012/JPEGImages/2012_002128.jpg ... ~/VOC/VOCdevkit/VOC2012/JPEGImages/2009_000104.jpg ~/VOC/VOCdevkit/VOC2012/JPEGImages/2012_000212.jpg ``` ### 3. COCO datasets #### description of dataset directory suppose that COCO dataset location are `~/COCO` and COCO folder contains `annotations`, `val2017` folder here are each structure for annotations and val2017 **annotations** ```bash $ cd ~/COCO/annotations/ $ tree -L 1 . └── instances_val2017.json ``` **val2017** ```bash . ├── 000000000139.jpg ├── 000000000285.jpg ├── 000000000632.jpg ├── 000000000724.jpg ... ├── 000000581357.jpg ├── 000000581482.jpg ├── 000000581615.jpg └── 000000581781.jpg ``` #### make `*.names` file now make `*.names` file in `~/COCO/` refer [darknet `coco.names` file](https://github.com/pjreddie/darknet/blob/master/data/coco.names) ```bash person bicycle car motorbike aeroplane bus train truck boat traffic light fire hydrant stop sign parking meter bench bird cat dog horse sheep cow elephant bear zebra giraffe backpack umbrella handbag tie suitcase frisbee skis snowboard sports ball kite baseball bat baseball glove skateboard surfboard tennis racket bottle wine glass cup fork knife spoon bowl banana apple sandwich orange broccoli carrot hot dog pizza donut cake chair sofa pottedplant bed diningtable toilet tvmonitor laptop mouse remote keyboard cell phone microwave oven toaster sink refrigerator book clock vase scissors teddy bear hair drier toothbrush motorcycle potted plant dining table tv couch airplane ``` #### COCO datasets convert to YOLO format now execute example code. this example assign directory for saving `YOLO` label `~/YOLO/` and assign `manipast_path` is `./` **make YOLO folder** ```bash $ mkdir ~/YOLO ``` **COCO convert to YOLO** ```bash python3 example.py --datasets COCO --img_path ~/COCO/val2017/ --label ~/COCO/annotations/instances_val2017.json --convert_output_path ~/YOLO/ --img_type ".jpg" --manipast_path ./ --cls_list_file ~/COCO/coco.names >> COCO Parsing: |████████████████████████████████████████| 100.0% (36781/36781) Complete YOLO Generating:|████████████████████████████████████████| 100.0% (4952/4952) Complete YOLO Saving: |████████████████████████████████████████| 100.0% (4952/4952) Complete ``` #### Result now check result files (`~/YOLO/`, `./manifast.txt`) **`~/YOLO/`** ```bash . ├── 000000000139.txt ├── 000000000285.txt ├── 000000000632.txt ├── 000000000724.txt ... ├── 000000581206.txt ├── 000000581317.txt ├── 000000581357.txt ├── 000000581482.txt ├── 000000581615.txt └── 000000581781.txt ``` **`000000581781.txt`** ```bash 46 0.446 0.557 0.465 0.209 46 0.517 0.851 0.363 0.128 46 0.939 0.05 0.122 0.071 46 0.786 0.027 0.11 0.054 46 0.171 0.247 0.19 0.139 46 0.865 0.773 0.27 0.372 46 0.111 0.552 0.215 0.333 46 0.51 0.744 0.376 0.207 46 0.811 0.377 0.25 0.36 46 0.955 0.388 0.09 0.181 46 0.195 0.333 0.153 0.224 46 0.036 0.183 0.065 0.357 46 0.496 0.45 0.389 0.132 46 0.499 0.52 0.998 0.956 ``` **`./manifast.txt`** ```bash ~/COCO/val2017/000000289343.jpg ~/COCO/val2017/000000061471.jpg ~/COCO/val2017/000000472375.jpg ~/COCO/val2017/000000520301.jpg ~/COCO/val2017/000000579321.jpg ~/COCO/val2017/000000494869.jpg ... ~/COCO/val2017/000000097585.jpg ~/COCO/val2017/000000429530.jpg ~/COCO/val2017/000000031749.jpg ~/COCO/val2017/000000284282.jpg ``` ### TODO **Refactoring (Release v2.0.0)** - [ ] Add strict Type Annotation in code - [ ] Separate role in class more strictly - [ ] Rewrite README.md for more helpful use first - [ ] Resolve the problem that strictly validation check when the trivial error - [ ] Supported Multiprocessing - [ ] Skip object class that don't want