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There are several kind of image classification:
- Binary classification
- Multiclass classification
- Multi label classification
Image generation method for training
- image.ImageGenerator.flow_from_directory()
- image.ImageGenerator.flow()
Various models for training (built on model)
- Xception
- VGG16
- VGG19
- Resnet50
- InceptionV3
- InceptionResNetV2
- MobileNet
- DenseNet
- NASNet
- MobileNetV2
Keras built in models usually have pre-trained weight on Imagenet, which significantly speeds up training, but those weights are only available for some image sizes.
There are two techniques to feed image files for prediction in Keras:
keras.preprocessing.image.flow_from_directory()keras.preprocessing.image.flow()
Simple Tutorials
- Simple Binary Image Classifier with Keras with flow_from_directory()
- Simple Binary Image Classifier with Keras with flow()
- Simple Multiclass Image Classification with Keras and flow_from_directory()
- Simple Multiclass Image Classification with Keras and flow()
- Simple Multi Label Image Classification with Keras and flow()
Reference
- Binary Classification / Binomial Classification https://en.wikipedia.org/wiki/Binary_classification
- Multi Class Classification / Multinomial Classification https://en.wikipedia.org/wiki/Multiclass_classification
- Multi Label Classification https://en.wikipedia.org/wiki/Multi-label_classification
- keras.preprocessing.image.flow_from_directory()
- keras.preprocessing.image.flow()
- Guide to Multi-class Multi Label Classification with Neural Networks https://www.depends-on-the-definition.com/guide-to-multi-label-classification-with-neural-networks/