This repo contains code for classifying caricature and cartoon images using Convolutional neural network(CNN) and transfer learning.
- A CNN based model trained on augmented 3.5k original images.
- Model takes advantage of transfer learning and uses pre-trained VGG16 model weights.
- Trained model is able to achieve 87% accuracy.
- Developed as a sub-project to filter cartoons from caricature dataset.
- Trained model can be found here.
Run below command if you don't have python3 installed
sudo apt-get install python3.6
Dependencies:
pip install tensorflow
pip install keras
pip install PyDrive
pip install numpy
pip install matplotlib
def load_image(filename):
img = image.load_img(filename, target_size=(224, 224))
img_tensor = image.img_to_array(img)
img_tensor = np.expand_dims(img_tensor, axis=0)
img_tensor /= 255.
return img_tensor
from keras.models import load_model
model = load_model('model.h5')
threshold = 0.2
if model.predict(load_image(img_name))[0][0] < threshold:
print('Caricature')
else:
print('Cartoon')
As you can see model works pretty well, and only gets confused with cartoon images containing a single face.
