(2014) Show, Attend and Tell: Neural Image Caption Generation with Visual Attention类比人看图说话:当人在解说一幅图片的时候,每预测一个字,会关注到图片上的不同位置。在解码器预测文字的时候,会关注到跟当前文字内容和图片最相关的位置。举例:a woman standing in a living room holding a Wii remote . ...
R. Zemel, Y. Bengio, Show, attend and tell: Neural image caption generation with visual attention, arXiv preprint arXiv:1502.03044. [2] Q. You, H. Jin, Z. Wang, C. Fang, J. Luo, Image captioning with semantic attention, in: IEEE Conference on Computer Vision and Pattern Recognition,...
## 完成dataload import paddle from paddle.io import Dataset import numpy as np from sklearn.model_selection import train_test_split # 重写数据读取类 class CaptionDataset(Dataset): # 构造函数,定义函数参数 def __init__(self,csvData,word2id_dict,h5f,maxlength = 40,mode = 'train'): self....
通过datasets.py里面的CaptionDataset类,我们创建了一个读取数据的类,这个类继承于 PyTorchDataset,需要实现__len__和__getitem__两个方法。__len__表示整个数据总数,我们定义为所有的字幕总数,__getitem__表示读取对应的图片,字幕以及字幕长度。CaptionDataset的代码已经实现完成,感兴趣的同学可以自行阅读。
在图像字幕(image caption)技术开发中,微软早在2017年就首次发布了强大的“SeeingAI”APP,它可以通过...
Figure 2. Image captioning architecture with attention [2] Implementation inarcgis.learn Inarcgis.learn, we have used the architecture shown in Figure 2. It currently supports only theRSICD dataset[1] for image captioning due to the lack of remote sensing captioning data. Other datasets are avai...
--dataset_folder The folder containing all the samples. (Default "./dataset") Used only in training mode --image_path The absolute path of the image that we want to retrieve the caption. (Default '') Used only in evaluation mode --splits Fraction of data to be used in train set, va...
CoCoDataset类中的getitem方法用于确定图像标注对在合并到批处理之前应如何进行预处理。 当数据加载器处于训练模式时,该方法将首先获得训练图像的文件名(path)及其对应的标注(caption)。 Image Pre-Processing(图像预处理) # Convert image to tensor and pre-process using transformimage=Image.open(os.path.join(sel...
CoCoDataset类中的getitem方法用于确定图像标注对在合并到批处理之前应如何进行预处理。 当数据加载器处于训练模式时,该方法将首先获得训练图像的文件名(path)及其对应的标注(caption)。 Image Pre-Processing(图像预处理) 代码语言:javascript 复制 # Convert image to tensor and pre-process using transform ...
Image captionDeep learningLSTMCNNAttentionImage captioning aims to describe the content of images with a sentence. It is a natural way for people to express their understanding, but a challenging and important task from the view of image understanding. In this paper, we propose two innovations to...