See the live demo now by clicking here.
Clone the repository by downloading the code or using this at a prompt:
git clone https://github.com/KatherineMossDeveloper/Midnight-Train.git
Open the project in Pycharm, or your preferred editor, and start the local development server:
npm run dev
Open the app in your browser at...
http://localhost:3000
This project was inspired by a research paper: Salami, H., McDonald, M. A., Bommarius, A. S., Rousseau, R. W., & Grover, M. A. (2021). In Situ Imaging Combined with Deep Learning for Crystallization Process Monitoring: Application to Cephalexin Production. Organic Process Research & Development, 25, 1670–1679.
The scientists who wrote the paper trained ResNet models with ImageNet weights on the OpenCrystalData dataset. The models were trained to do binary classification of images of crystals, designating them as either CEX (a.k.a., “cephalexin antibiotic,” a good thing) or PG (a.k.a. “phenylglycine,” a bad thing).
The Georgia Project, in this same GitHub site, recreates their work, then it stores details in a database.
Midnight train, in turn, pulls these details from the database and creates graphs in order to study the dataset. Here is Midnight Train's detailed documentation.
Go to the main doc file
If you found an issue or would like to make a suggestion for an improvement to the code or documentation, please click on the issue tab on the project page and leave me a note. If you like this project, leave a star.
None.
For more details about this project, feel free to reach out to me at katherinemossdeveloper@gmail.com or my account on LinkedIn. My time zone is EST in the U.S.