Make the Data and Models Quality easy for everyone
Easequality is basically a High level Wrapper which connects your Data/Model with various Quality Tools, Hence you can evaluate the Data/Model quality with few lines of code.
- The code will be released soon! Please stay tuned! ๐
To install
git clone https://github.com/Usama3059/easequality.git
cd Easequality
To run tests, run the following command, we are evaluating on the BCCD Dataset and Yolov5
#Example for Yolov5 Model
from yolo import yolo_quality
cls_dict = {
0: 'RBC',
1: 'WBC',
2: 'Platelets'}
yolo = yolo_quality( train_dir_path='train',
test_dir_path='valid',
model_path='model.pt',
class_dict = cls_dict)
yolo.result()
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Supports MSCOCO, PascalVOC, Yolo, Yolo Darknet etc
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Supports Fastai Classification
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Supports Timm Models
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Supports Detectron2
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Supports Yolov5
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Code release for everyone
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Quick Summary
Hi, I'm Usama Altaf Zahid mainly work as Computer vision Engineer. I like working with AI models and building Computer vision based problem solving products. This repo is basically a helpful tool to easily and rapidly evaluate and improve the Data/Model Quality, Hence to build more robust Models with very less training process iterations
Contributions are always welcome!
If you have any feedback, please reach out to us at [email protected]