deep_food.py 文件源码

def pred():
  item_index = pickle.loads(open("cookpad/item_index.pkl", "rb").read())
  index_items = { index:item for item, index in item_index.items()}
  model = build_model()
  model = load_model(sorted(glob.glob('models/model00060.model'))[-1]) 
  target_size = (224,224)
  dir_path = "to_pred/*"
  max_size = len(glob.glob(dir_path))
  for i, name in enumerate(glob.glob(dir_path)):
    try:
      img = Image.open(name)
    except OSError as e:
      continue
    print(i, max_size, name.split('/')[-1])
    w, h = img.size
    if w > h :
      blank = Image.new('RGB', (w, w))
    if w <= h :
      blank = Image.new('RGB', (h, h))
    blank.paste(img, (0, 0) )
    blank = blank.resize( target_size )
    Xs = np.array([np.asanyarray(blank)])
    result = model.predict(Xs)
    ares   = [(index_items[index], w) for index, w in enumerate(result.tolist()[0]) ]
    for en, (item, w) in enumerate(sorted(ares, key=lambda x:x[1]*-1)[:10]):
      print(en, item, w)