Detect and decode the CCT (Circular Coded Target).
<1> python 3.7 (I don't know whether other python version would work correctly, you can have a try.)
<2> opencv-python
<3> pillow
<4> numpy
<5> matplotlib
<6> progress
<7> ... (maybe others, you can follow the error infomation to 'pip install xxx' them.)
- Draw CCT images: DrawCCT.py
usage:
<1> cd root_path <2> python DrawCCT.py --bit_n=9 --size=400 --color=black
- Detect and decode CCT: CCTDecodeRelease.py
which can decode CCT from the signal image, or you can use it to decode the CCT images in the same folder.
usage:
<1> cd root_path <2> python CCTDecodeRelease.py --filename=cct12_6.png --bit_n=12 --threshold=0.7 // for single image --color=black // select the color of CCT mark (white over black / black over white) python CCTDecodeRelease.py --batch=True --bit_n=8 --save_folder=./result/ --threshold=0.93 // for images in same folder --color=black
Actually, there are some args are default value which can be ignored if you follow my data construction. The whole args are listed as follows:
batch=False, // batch processing
bit_n=12, // the bit number of CCT image
filename=None, // image name
save_folder='./result/', // the folder for saving the processed images
src_folder='./data/', // the folder which contains the source images
threshold=0.8 // the threshold for CCT detecion, which is between 0 and 1.
color=white // the color of CCT mark (white over black / black over white)
So, you can change these args as you whish. But remember to write it correctly and don't foget the '--' before each arg.
- Decode CCT from video: DecodeCCTFromVideo.py
usage:
<1> cd root_path <2> python DetectCCTFromVideo.py --bit_n=12 --threshold=0.7 --color=white