Facial Recognition

Introduction

Class: W207

Team Name: Choo-Choo-Train

Team Members:

1. Jordan Meyer
2. Amit Thiruvengadam
3. Sweeta Bee
4. Leon Gutierrez

Instruction to run code

Preparation

• In the data folder unzip "facial-keypoints-detection.zip"
• This will create a folder called "facial-keypoints-detection". Move the contents of this folder, namely, IdlookupTable.csv, SampleSubmission.csv, train.csv, test.csv into the "data"" folder
• Next unzip training.zip and test.zip and move training.csv and test.csv into the data folder
• Your folder structure should now look like this:

Choo-Choo-Train
      |_data
           |_IdLookupTable.csv
           |_SampleSubmission.csv
           |_training.csv
           |_test.csv
           |_models (empty folder)
           |_analysis (folder with some content)
           |_augment (empty folder)
      |_notebooks
           |_ main.ipynb
           |_ image_analysis.ipynb
      |_README.md (this file)
      |___init__.py

Note: Please rename the main folder to cct. It should now look like this

cct
  |_data
       |_IdLookupTable.csv
       |_SampleSubmission.csv
       |_training.csv
       |_test.csv
       |_models (empty folder)
       |_analysis (folder with some content)
       |_augment (empty folder)
  |_notebooks
       |_ main.ipynb
       |_ image_analysis.ipynb
  |_README.md (this file)
  |___init__.py

Creating models

• Models take ~15hrs to generate on a GPU and must be run on a High RAM machine
• Move the entire folder structure to Google Drive and place it in your Colab Notebook folder. It should now look like this:

|_drive
      |_MyDrive
            |_Colab Notebooks
                          |_cct

• open main.ipynb from the notebooks folder and follow instruction on first cell
• It creates a file called CNNMySubmission.csv that can be submitted for the Kaggle competition

cct
  |_data
       |_CNNMySubmission.csv

Analysis

• open image_analysis.ipynb from the notebooks folder and run all cells