readme: ---
  license: apache-2.0
  ---
  
  MobileNet V2 model from Torchvision fine-tuned for FOOD101 dataset. Checkpoint trained for 30 epoches using https://github.com/AlexKoff88/mobilenetv2_food101.
  
  Top-1 accuracy is 76.3% but one can do better.
  
  The main intend is to use it in samples and demos for model optimization. Here is the advantages:
  - FOOD101 can automatically downloaded without registration and SMS.
  - It is quite representative to reflect the real world scenarios.
  - MobileNet v2 is easy to train and lightweight model which is also representative and used in many public benchmarks.
  
  Here is the code to load the checkpoint in PyTorch:
  
  ```python
  import sys
  import os
  
  import torch
  import torch.nn as nn
  import torchvision.models as models
  
  FOOD101_CLASSES = 101
  
  def fix_names(state_dict):
      state_dict = {key.replace('module.', ''): value for (key, value) in state_dict.items()}
      return state_dict
  
  model = models.mobilenet_v2(num_classes=FOOD101_CLASSES)  
  
  if len(sys.argv) > 1:
      checkpoint_path = sys.argv[1]
  
      if os.path.isfile(checkpoint_path):
          print("=> loading checkpoint '{}'".format(checkpoint_path))
          
  
          checkpoint = torch.load(checkpoint_path)
          weights = fix_names(checkpoint['state_dict'])
          model.load_state_dict(weights)
  
          print("=> loaded checkpoint '{}' (epoch {})"
                  .format(checkpoint_path, checkpoint['epoch']))
  ```