import argparse from PIL import Image import torch import matplotlib.pyplot as plt import numpy as np import cv2 import pickle from utils import CocoEvalLoader, to_var, show_images from adaptive import Encoder2Decoder from build_vocab import Vocabulary from torch.autograd import Variable from torchvision import transforms def main(): pretrained = 'models/adaptive-1.pkl' vocab_path = './data/vocab.pkl' with open(vocab_path, 'rb') as f: vocab = pickle.load(f)

Define model and load pretrained

model = Encoder2Decoder(256, len(vocab), 512)
model.load_state_dict(torch.load(pretrained, map_location={'cuda:1':'cuda:0'}))
model.eval()
# Image transformation
transform = transforms.Compose([
    transforms.ToTensor(),
    transforms.Normalize((0.485, 0.456, 0.406),
                         (0.229, 0.224, 0.225))])
image = Image.open('./data/test/1.jpg')
image = image.resize([224, 224], Image.LANCZOS)
image = transform(image).unsqueeze(0)
image_tensor = Variable(image, volatile=True)
generated_captions, _, _ = model.sampler(image_tensor)
captions = generated_captions.data.numpy()
sampled_ids = captions[0]
sampled_caption = []
for word_id in sampled_ids:
    word = vocab.idx2word[word_id]
    if word == '<end>':
        break
    else:
        sampled_caption.append(word)
sentence = ' '.join(sampled_caption)
# return sentence
print (sentence)

if name == 'main': main() 出错：TypeError: torch.index_select received an invalid combination of arguments - got (torch.FloatTensor, int, !torch.cuda.LongTensor!)

please help! Thanks

yufengm / Adaptive

When test has a problem,please help #10

Define model and load pretrained