Real-vs-AI-in-Shoe-Imagery

Supervised Learning Project

Dataset: https://www.kaggle.com/datasets/sunnykakar/shoes-dataset-real-and-ai-generated-images

Work:

1. Prepare data in PyTorch format. (Omar)
2. Preprocessing. (Fawzi, if needed)
3. Create models. (All)
4. Report. (Wesam)

Models:

• SciKit Learn -Naive Bayes. ✅ -KNN. ✅ -SVM. ✅ -Decision Trees. ✅ -Random Forest. ✅ -Logistic Regression. ✅

XGBoost ANN/CNN.

Stages:

1. Distribute all data into train/valid/test folders with its labels.
2. preprocessing: 2.1 convert labels into 0/1 (int64)
3. extract features.
4. create models (in order).
5. evaluation.
6. report.

Done:

1. Distribute all data into train/valid/test folders with its labels.
2. preprocessing: 2.1 convert labels into 0/1 (int64)