Transfer Learning. This is when you borrow from an existing model by using parts of it in a new model. This is almost always better than training a new model from scratch (i.e., knowing nothing). As you will see, you can always fine-tune this second-hand knowledge to the specific ta...
我们将图像作为输入,并使用深度学习模型预测其描述。 完整代码:https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/image_captioning 我们使用预训练的 resnet-152模型作为编码器,而解码器是LSTM网络。 要运行本例中给出的代码,首先要必须有一个工作的python环境,最好安装了anaconda。然后...
完整代码:https://github.com/yunjey/pytorch-tutorial/tree/master/tutorials/03-advanced/image_captioning 我们使用预训练的resnet-152模型作为编码器,而解码器是LSTM网络。 要运行本例中给出的代码,首先要必须有一个工作的python环境,最好安装了anaconda。然后运行以下命令以安装其他需要的库。 01git clone https:...
Transfer Learning. This is when you borrow from an existing model by using parts of it in a new model. This is almost always better than training a new model from scratch (i.e., knowing nothing). As you will see, you can always fine-tune this second-hand knowledge to the specific ta...
cd pytorch-tutorial/tutorials/03-advanced/image_captioning/pip install -r requirements.txt 设置完系统后,就该下载所需的数据集并且训练模型了。这里我们使用的是MS-COCO数据集。可以运行如下命令来自动下载数据集: chmod +x download.sh./download.sh 现在可以继续并开始模型的构建过程了。首先,你需要处理输入: ...
git clone https://github.com/pdollar/coco.git cd coco/PythonAPI/ make python setup.py build python setup.py install cd ../../ git clone https://github.com/yunjey/pytorch-tutorial.git cd pytorch-tutorial/tutorials/03-advanced/image_captioning/ pip install -r requirements.txt ...
git clone https://github.com/yunjey/pytorch-tutorial.gitcd pytorch-tutorial/tutorials/03-advanced/image_captioning/ pip install -r requirements.txt 设置完系统后,就该下载所需的数据集并且训练模型了。这里我们使用的是MS-COCO数据集。可以运行如下命令来自动下载数据集: ...
https://github.com/sgrvinod/a-PyTorch-Tutorial-to-Image-Captioning作者对项目的原理进行了比较详细的介绍,为了方便大家理解,我再将其中的关键内容翻译一遍,之后再对代码进行介绍。 1.运行环境 1.1 我的环境 在进行详细的介绍之前,先介绍一下我的运行环境,大家可以以此作为参考。在配置环境的时候需要根据自己的显卡...
git clone https://github.com/pdollar/coco.gitcdcoco / PythonAPI /cd../../git clone https://github.com/yunjey/pytorch-tutorial.gitcdpytorch-tutorial / tutorials / 03-advanced / image_captioning /pip install -r requirements.txt 设置好系统后,应下载训练模型所需的数据集。这里我们将使用MS-COCO...
神经对话 2 模型可以在github.com/deep-learning-with-pytorch/ImageCaptioning.pytorch找到。我们可以将一组图像放在data目录中,并运行以下脚本: pythoneval.py --model ./data/FC/fc-model.pth--infos_path ./data/FC/fc-infos.pkl --image_folder ./data ...