k210 face detection demo

I implement face detection based on the idea of yolo network in Kendryte K210. ps : this model only 500kb

Usage

environmental preparation

you should install python package:

tensorflow 1.12 imgaug scikit-image numpy opencv-python matpltlib scipy tqdm

train model

prepare dataset and make train list

cd k210-face-detection
wget http://tamaraberg.com/faceDataset/originalPics.tar.gz
mkdir FDDB
tar -zxvf originalPics.tar.gz -C FDDB
wget http://vis-www.cs.umass.edu/fddb/FDDB-folds.tgz
tar -zxvf FDDB-folds.tgz -C FDDB
python3 tools/make_list.py --fddb_dir FDDB --ann_dir FDDB/FDDB-folds

now your data fold have train.list

NOTE: When generate the train.list I set the box width and height only half. if you want use the normal value to train, please remove the comment in tools/make_list.py line 47

train
```
make train_pureconv ILR=0.001 MAXEP=20 IAA=false
```
ILR : the init learning rate

MAXEP : max epoch

IAA : whether to use data augmenter

NOTE: you can use CKPT:xxxxx to continue train

example:
```
make train_pureconv CKPT=log/20190216-152633 ILR=0.0005 MAXEP=20 IAA=true
```
And you can use tensorboard --logdir log to look the record

test model

make inference PB=Freeze_save.pb

export pb

freeze ckpt
```
make freeze CKPT=log/20190216-154422 
```
now your fold will have Freeze_save.pb
use kendryte-model-complier to complie pb file

you can use my script (you should modify MODELCMP):
```
make kmodel_convert PB=Freeze_save.pb MODELCMP=~/Documents/kendryte-model-compiler
```
or refer to see the kendryte-model-compiler

modfiy k210 code

copy weights array to code

cp ~/Documents/kendryte-model-compiler/build/gencode_output.* K210_code/

compile the code

you can refer to the documents k210 use in windows or k210 use in linux

And you can find some useful article in my bolg.
down load program

now you can use kflash.py down load the program