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关于 numpy 中的 axis 和 pytorch 中的 dim 123456789101112131415import numpy as nparray = np.random.randint(low=0, high=6, size=(3, 4))print(array.shape, array)# (3, 4) [[5 3 0 4]# [4 3 1 0]# [2 0 3 2]]array0 = array.sum(axis=0, keepdims=True)print(array0.shape, array0)# (1, 4) [[11 6 4 6]]array1 = array.sum(axis=1, keepdims=True)print(array1.shape, array1)# (3, 1) [[12]# [ 8]# [ 7]] 123456789101112131415import torchtensor = torch.randint(low=0, high=6, size=(3, 4))prin ...

Reference Transforms v2: End-to-end object detection/segmentation example Transforms v2: End-to-end object detection/segmentation example Youtube video introducing COCO COCO Dataset Format - Complete Walkthrough Blog that introduces COCO format COCO format , what and how Waht is COCO format Introduction The COCO (Common Objects in Context) format is a standard format for storing and sharing annotations for images and videos. It was developed for the COCO image and video recognition cha ...

Gaussian Error Linear Unit (GELU) Arxiv link to the paper of GELU Gaussian Error Linear Unit (GELU) Definition of GELU GELU(x)=xP(X≤x)=xΦ(x)=x⋅12[1+erf(x/2)]{\rm GELU}(x) = xP(X \leq x) = x\Phi(x) = x\cdot \frac{1}{2} \left[ 1+ {\rm erf}(x/\sqrt2) \right] GELU(x)=xP(X≤x)=xΦ(x)=x⋅21​[1+erf(x/2​)] Where Φ(⋅)\Phi(\cdot)Φ(⋅) denotes cumulative distribution function (CDF) for normal distribution and erf(⋅){\rm erf}(\cdot)erf(⋅) is error function. Derivative of GELU ddxGELU(x)=ddx[x⋅Φ(x)]=Φ(x)+x ...

How to use Google Scholars 谷歌学术检索论文如何指定多个来源 Google Scholar 谷歌学术文献检索技巧总结 TGRS 1Segmentation (source: "Transactions on Geoscience and Remote Sensing") ICCV 1Segmentation (source: "International Conference on Computer Vision") CVPR 1Segmentation (source: "Computer Vision and Pattern Recognition") NeurIPS 1Segmentation (source: "Advances in Neural Information Processing Systems") AAAI 1Segmentation (source: "Proceedings of the AAAI Conference on Artificia ...

SSH, Secure Shell 查看已有公钥 12cd ~/.ssh # 进入目录cat id_rsa.pub # 显示公钥 1cat ~/.ssh/id_rsa.pub # 显示公钥 生成新的密钥 12345678910111213ssh-keygen -t rsa -b 4096 -f ~/.ssh/newsshkey# 参数说明:# -t rsa 指定加密方式为RSA# -b 4096 密钥长度（bit）# -f 指定密钥文件名, 默认为 id_rsa# 各个参数都可以不填, 使用默认参数ssh-keygen# 建议加上这些参数ssh-keygen -t rsa -C xxx@xxx.com# 这里的 xxx@xxx.com 只是用于生成的 sshkey 的名称, 并不要求具体命名为某个邮箱 将公钥上传至服务器 SSH配置密钥登录以及简单的安全设置 123ssh-copy-id -i ~/.ssh/newsshkey.pub -p port User@HostName# -i ~/.ssh/newsshkey.pub 指定密钥文件公钥, 注意后缀为.pub, 这是 ...

ISPRS-Potsdam Prepare Dataset: ISPRS-Potsdam | mmsegmentation The Potsdam dataset is for urban semantic segmentation used in the 2D Semantic Labeling Contest - Potsdam. The dataset can be requested at the challenge homepage. You will get a file named utf-8' 'Potsdam.zip, and unzip this file to get a folder named Potsdam which contains 10 files: 1234567891011Potsdam├── 1_DSM.rar├── 1_DSM_normalisation.zip├── 2_Ortho_RGB.zip <--├── 3_Ortho_IRRG.zip├── 4_Ortho_RGBIR.zip├── 5_Labels_all.zip├── 5_ ...

ExifTool ExifTool Command-Line Examples Pillow Pillow documentation PIL.Image.open PIL.Image.save PIL.Image.convert 12conda install pillowimport PIL open images in a folder 12345678910111213141516171819202122232425262728import osimport globfrom PIL import Imageimport matplotlib.pyplot as pltpath2image = r"path/to/images"path2mask = r"path/to/masks"image_paths = glob.glob(os.path.join(path2image, '*.png'))image_names = [os.path.basename(result_path) for result_path i ...

TOC You can also create TOC (Table Of Contents) by inserting [TOC] to your markdown file. For example: [TOC] Hyperlink With {target="_blank"} added, the hyperlink will be opened in a new Tab Markdown Preview Enhanced{target="_blank"} Otherwise, it will be opened in current Tab Markdown Preview Enhanced{target="_blank"} You can right click and Open in Browser to try the two hyperlinks above. Emoji & Font-Awesome :smile:, :fa-car: Front-matter 123456789 ...

Learning material Youtube video tutorials PyTorch Lightning Tutorials | Aladdin Persson{target="_blank"} The official document lightning ai docs{target="_blank"} The official document > Level Up Level Up: Basic skills{target="_blank"} Level Up: Intermediate skills{target="_blank"} Level Up: Advanced skills{target="_blank"} Level Up: Expert skills{target="_blank"} LightningModule Lightning Module{target="_blank"} Log ...

Run Swin Transformer for Semantic Segmentation on Colab Swin-Transformer-Semantic-Segmentation | GitHub mmsegmentation | GitHub mmsegmentation/…/get_started.md#install-on-google-colab | GitHub get_started/installation | mmcv Swin Transformer算法环境配置（语义分割）| ZhiHu MMSegmentation_Tutorial.ipynb | Colab install mmcv and mmsegmentation 12!pip install openmim!mim install mmcv Use mmcv, not mmcv-full, to install the full version, because it took me so long that I canceled the installation. MMCV contains ...