deepsense-ai / Keras Pytorch Avp Transfer Learning
We pit Keras and PyTorch against each other, showing their strengths and weaknesses in action. We present a real problem, a matter of life-and-death: distinguishing Aliens from Predators!
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Keras vs. PyTorch: Alien vs. Predator recognition with transfer learning
Featured in deepsense.ai blog post Keras vs. PyTorch: Alien vs. Predator recognition with transfer learning, in which we discuss the differences. Code is in two Jupyter Notebooks:
See also the upcoming webinar (10 Oct 2018), in which we walk trough the code.
For plug&play interactive code, see the Neptune versions with fancy charts or these Kaggle Kernels:
- Transfer learning with ResNet-50 in Keras - Kaggle Kernel
- Transfer learning with ResNet-50 in PyTorch - Kaggle Kernel
Data
See also: Alien vs. Predator images | Kaggle. In general, there are 447 images for each class, split into two classes. Examples:
Requirements
If you want to run the code, see the requirements:
- Common:
- jupyter==1.0.0
- matplotlib==2.2.3
- Pillow==5.2.0
- h5py==2.8.0
- Keras:
- tensorflow==1.10.1
- Keras==2.2.2
- PyTorch:
- torch==0.4.1
- torchvision==0.2.1
Webinar info
- Link to the webinar (10 Oct 2018, 5 PM CEST)
- Slides from the webinar
- deepsense.ai's articles about Keras and PyTorch:
- Notebooks in Neptune
- Workshops:
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