Code and trained model for Computer Vision for Segmentation and Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Datase

Code and trained models for the semantic segmentation FCN and Instance segmentation (GES net) neural nets used in:

Computer Vision for Recognition of Materials and Vessels in Chemistry Lab Settings and the Vector-LabPics Dataset

The nets receive an image of material in vessel and segment and classify all the region in the image corresponding to vessels and various of material phases inside them

https://chemrxiv.org/articles/Computer_Vision_for_Recognition_of_Materials_and_Vessels_in_Chemistry_Lab_Settings_and_the_Vector-LabPics_Dataset/11930004

Basically the net contained both the model and the trained weight  and can be run as-is with no training

for  semantic segmentation  net (PSP)

and Generator evaluator selector Net (Ges net)