Final Year Project

Python version used : 3.6.0

python3 OCRSentiment.py

Real-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV.

• IMDB gender classification test accuracy: 96%.
• fer2013 emotion classification test accuracy: 66%.

python3 video_emotion_color_demo.py

python3 image_emotion_gender_demo.py <image_path>

e.g.

python3 image_emotion_gender_demo.py ../images/test_image.jpg

Steps to run project:- Step 1:- Download project from https://github.com/AnkurKarmakar/Multi-Modal-Image-Sentiment-Analysis Extract the zip folder and place the entire project folder in any drive except C drive.

Step 2:- Install Python 3.6.0 64 bit from https://www.python.org/downloads/release/python-360/(Note:- Other versions will cause problems with the tensorflow version used)

Step 3:- Download site-packages.rar from https://drive.google.com/file/d/1yBVfiMuq6DI8gIF4z__E_gCmwSwEL4uu/view?usp=sharing and extract it into C:\Users<UserName>\AppData\Local\Programs\Python\Python36\Lib\

Step 4:- Go to project folder where requirements.txt is present.Then open cmd there and type pip install -r requirements.txt

Step 5:- Download Tesseract from https://sourceforge.net/projects/tesseract-ocr-alt/files/tesseract-ocr-setup-3.02.02.exe/download and then install it

Step 6:- Go to project folder. Inside src folder there is UI.exe. Run it and program will run. After the UI pops up click on Browse to select image and then click on Analyze.

• Download the fer2013.tar.gz file from here

• Move the downloaded file to the datasets directory inside this repository.

• Untar the file:

tar -xzf fer2013.tar

• Run the train_emotion_classification.py file

python3 train_emotion_classifier.py

• Download the imdb_crop.tar file from here (It's the 7GB button with the tittle Download faces only).

• Move the downloaded file to the datasets directory inside this repository.

• Untar the file:

tar -xfv imdb_crop.tar

• Run the train_gender_classification.py file

python3 train_gender_classifier.py