YAYA - Yet Another YOLO Annoter
with QT5 widgets
gui, and ...
- Rewritten in python,
- Checks for errors of overriding boxes,
- Displays image properties
size
,hue
,saturation
,brightness
, - Displays annotations properties,
average size
,class numbers
, - Uses given YOLOv4 detectors to detect every file and store detections!
- Calculate metrics TP,TN,FP,FN,Precision,Recall for every photo!
- Auto-annotation with YOLOv4 detectors feature added - use yolo to detect and describe annotations of your image,
- Manual Yolo detection by presing 'd' - to check YOLO with original data,
- You can use standard YOLOv4 (MSCOCO) or your custom YOLOv4
pip install -r requirements
Install YOLOv4 darknet library libdarknet.so
in your operating system (https://github.com/AlexeyAB/darknet) for usage of custom YOLOv4 detectors.
- Inside directory
ObjectDetectors/
create your detector directory (for exampleyolov4custom
). - Copy all YOLOv4 detector files :
yolo.cfg
,yolo.data
,yolo.names
,yolo.weights
(names should be identicall) - Got it! Now you can use this detector!
Found detectors list is also shown at the program start, example :
python ./yolo-annotate.py -i input/
DEBUG:root:Logging enabled!
/usr/local/lib/libdarknet.so
INFO:root:(Found detector) 0 - /home/spasz/python/aisp-tools/yaya/ObjectDetectors/yolov4custom/yolo.
To load all test images from input
directory and start application, you can use command
./yolo-annotate.py -i input/
LPM - create annotation
d - run detector
r - remove annotation
c - clear all annotations
s - save all (if errors not exists)
arrow -> or . - next image
arrow <- or , - previous image
usage: yolo-annotate.py [-h] -i INPUT [-c CONFIG] [-on] [-yc] [-v]
optional arguments:
-h, --help show this help message and exit
-i INPUT, --input INPUT
Input path
-c CONFIG, --config CONFIG
Config path
-on, --onlyNewFiles Process only files without detections file.
-yc, --yoloCustom Use custom YOLO.
-v, --verbose Show verbose finded and processed data
[!DEPRECATED! - Use release/v0.6-OpenCV
for old OpenCV version] Yet Another yolo annotation program. Yolo_mark clone with openCV gui, but ...
- Rewritten in python,
- Checks for errors of overriding boxes,
- Auto-annotation feature added - use yolo to detect and describe annotations of your image,
- Manual Yolo detection by presing 'd' - to check YOLO with original data,
- You can use standard YOLOv4 (MSCOCO) or your custom YOLOv4