Project: Particle Sharpness Analysis In Python
Developed a methodology to quantitatively and objectively define particle sharpness with the range of 0 to 1
Applied data analysis skills in python language for image processing with modules: OpenCV, Pillow(PIL), Numpy, Matplotlib, and used them to crop images, to invert images color, and to detect particle edges Mentored by Chevron with the ShapesGenCode in Matlab to build the dataset of over 400 images
Collected, cleaned and provided the sequential model by modules: Scipy, Imutils, Glob, Itertools, Os, Keras, Tensorflow, Pandas, Sklearn, tqdm. Trained the model with 50 EPOCHS and achieved 40% for validating accuracy
Created the information link between deep learning to particle sharpness classification