This code is used for Morgan State University research. Dr. Rahman facilitated this research. This research is designed to help doctors better detect diseases in humans using ML. First, doctors compleate surveys via Amazon Mturk. Next, some algorithms get all the useful data. Lastly, this data is then used as inputs for a machine learning algorithm.
Note: Ensure Pandas is version 1.3, or greater
- To run the code run:
py3 CollectAnnotations.py fileLocation.csv
.
*NOTE* Substitutepy
with whatever your system requires to run python. - CollectAnnotations.py can take as many batch file command line arguments as needed.
- CollectAnnotations.py MUST recieve at least one command line argument. Each argument MUST be a csv file.
- There are two optional arguments -s and -h. -h means Help. If -h is anywhere in the list of args a help message is printed, then the python WILL exit with error code 0. -s is the location of a folder must where all the results will be saved.
- To run the code:
py3 createBatches.py batchLocation.csv -l [number]
- createBatches.py MUST take -l as an argument. It is the index that createBatches should start from.
- -s is an optional argument. It is the location where the results from createBatches.py will be saved. If it is not passed a Batches folder will be created and all output files will be saved there.
- -h means help. If this argument is anywere in the list of arguments a help message will be printed and the code will exit with error code 0.
- -c is the index to end at and it is exclusive. The value to end at is calulated by adding -l's values + -c's value. If -c is not passed 101 is assumed.
py3 CollectAnnotations.py fileLocation.csv
py3 CollectAnnotations.py fileLocation.csv fileLocation2.csv -a \otherFileLocation\
py3 CollectAnnotations.py -h
py3 createBatches.py batchLocation.csv -l [number]
py3 createBatches.py batchLocation.csv -l [number] -s [filePath/]
py3 createBatches.py batchLocation.csv -l [number] -c [number]