| #!/usr/bin/env python | |
| # see http://socialdatablog.com/extract-pdf-annotations.html | |
| myxkfolder="/home/steve/xk/" #you need to set this to where you want your to-dos to appear | |
| import poppler, os.path, os, time, datetime | |
| for root, dirs, files in os.walk('./'): | |
| for lpath in files: |
| Host NAT | |
| HostName 52.15.213.177 | |
| ForwardAgent yes | |
| StrictHostKeyChecking ask | |
| IdentityFile "C:\Users\Zach Tankersley\.ssh\id_rsa.pem" | |
| User ec2-user | |
| Host 10.0.1.12 | |
| ProxyCommand C:\Windows\System32\OpenSSH\ssh.exe -q -W %h:%p NAT | |
| ForwardAgent yes |
| """ | |
| Thiss script would convert a pre-trained TF model to a servable version for TF Serving. | |
| A pre-trained model can be downloaded here | |
| https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo | |
| Requirements: | |
| * A directory contains pretrained model (can be download above). | |
| * Edit three arguments `frozen_graph`, `model_name`, `base_dir` accordingly |
| # Pass the env-vars to MYCOMMAND | |
| eval $(egrep -v '^#' .env | xargs) MYCOMMAND | |
| # … or ... | |
| # Export the vars in .env into your shell: | |
| export $(egrep -v '^#' .env | xargs) |
| <html> | |
| <head> | |
| <title>Simple Line Graph using SVG and d3.js</title> | |
| <script src="http://mbostock.github.com/d3/d3.v2.js"></script> | |
| <style> | |
| /* tell the SVG path to be a thin blue line without any area fill */ | |
| path { | |
| stroke: steelblue; | |
| stroke-width: 1; | |
| fill: none; |
| const tf = require('@tensorflow/tfjs-node'); | |
| const Jimp = require('jimp'); | |
| // Directory path for model files (model.json, metadata.json, weights.bin) | |
| // NOTE: It can be obtained from [Export Model] -> [Tensorflow.js] -> [Download my model] | |
| // on https://teachablemachine.withgoogle.com/train/image | |
| const MODEL_DIR_PATH = `${__dirname}`; | |
| // Path for image file to predict class | |
| const IMAGE_FILE_PATH = `${__dirname}/example.jpg`; |
| <!DOCTYPE html> | |
| <html lang="en"> | |
| <head> | |
| <link rel="stylesheet" href="gh-fork-ribbon.css"> | |
| <link rel="stylesheet" href="style.css" /> | |
| <style> | |
| .right .github-fork-ribbon { | |
| background-color: #333; | |
| } | |
| </style> |
Inspired from: https://github.com/vigente/gerardus/wiki/Integrate-git-diffs-with-word-docx-files
Usage:
cd /path/to/your/repo/with/docx
sh -c "$(curl -fsSL https://gist.githubusercontent.com/ttimasdf/7965baab972b901c1f8349ce5fcb5e09/raw/setup-git-hook.sh)"Done!
| pip install bert-for-tf2 | |
| pip install bert-tokenizer | |
| pip install tensorflow-hub | |
| pip install bert-tensorflow | |
| pip install sentencepiece | |
| import tensorflow_hub as hub | |
| import tensorflow as tf | |
| import bert |
| # Having a requirements.txt file has follows | |
| torch==1.5.0 | |
| numpy==1.18.1 | |
| # Add channels. Last added is with the highest priorety | |
| conda config --add channels pytorch | |
| conda config --add channels conda-forge | |
| conda config --add channels anaconda | |
| # Install pip for fallback |