Exploring Methods of Image Classification—CIS 4930 (Data Mining) Final Project @ FSU
Python 100.00%
dmproj's Introduction
Exploring Methods of Image Classification: CIS 4930 @ FSU (Data Mining) Final Project
Group Members
Ben Bao
Cameron Ball
John Fleming
Steven Arteaga
Dependencies
Code tested on Python 3.9. While the code may work on other versions, we cannot guarantee that functionality.
For Predictions.py:
Tabulate
python3.9 -m pip install tabulate
joblib
python3.9 -m pip install joblib
NumPy
python3.9 -m pip install numpy
matplotlib
python3.9 -m pip install matplotlib
seaborn
python3.9 -m pip install seaborn
pandas
python3.9 -m pip install pandas
tensorflow
python3.9 -m pip install tensorflow
For DecisionTree.py:
joblib
python3.9 -m pip install joblib
pandas
python3.9 -m pip install pandas
scikit-learn
python3.9 -m pip install scikit-learn
For MLModelTrain.py:
tensorflow
python3.9 -m pip install tensorflow
matplotlib
python3.9 -m pip install matplotlib
For MobileNet.py:
tensorflow
python3.9 -m pip install tensorflow
matplotlib
python3.9 -m pip install matplotlib
keras
python3.9 -m pip install keras
For SVM.py:
scikit-image
python3.9 -m pip install scikit-image
NumPy
python3.9 -m pip install numpy
pandas
python3.9 -m pip install pandas
Usage
Download the dependencies if you do not already have them for Python 3.9.
Run Predictions.py to run the tests, get the model accuracies, and print the final results. To run it, you need a file that is too large to store on GitHub.
cd into src/, then run python3.9 MLModelTrain.py. This will generate the MLModelVGG16.h5 file.
If you receive errors about "local issuer certificates", you need to run Install Certificates.command that was given to you with your Python 3.9 installation.
After MLModelVGG16.h5 is generated, you can run Predictions.py. If you still want want to run the other model trainings from scratch, cd into src/, then run python3.9 <file>.
React
Typescript
Django
Laravel
Facebook
Microsoft
Google
Alibaba
D3
Tencent