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Repository: poloclub/cnn-explainer
Branch: master
Commit: d0971f9447ed
Files: 47
Total size: 649.6 KB
Directory structure:
gitextract_939_80p5/
├── .github/
│ └── workflows/
│ └── build.yml
├── .gitignore
├── LICENSE
├── README.md
├── deploy-gh-page.sh
├── package.json
├── public/
│ ├── assets/
│ │ └── data/
│ │ ├── model.json
│ │ └── nn_10.json
│ ├── global.css
│ └── index.html
├── rollup.config.js
├── rollup_start_dev.js
├── src/
│ ├── App.svelte
│ ├── Explainer.svelte
│ ├── Header.svelte
│ ├── article/
│ │ ├── Article.svelte
│ │ └── Youtube.svelte
│ ├── config.js
│ ├── detail-view/
│ │ ├── ActivationAnimator.svelte
│ │ ├── Activationview.svelte
│ │ ├── ConvolutionAnimator.svelte
│ │ ├── Convolutionview.svelte
│ │ ├── Dataview.svelte
│ │ ├── DetailviewUtils.js
│ │ ├── HyperparameterAnimator.svelte
│ │ ├── HyperparameterDataview.svelte
│ │ ├── Hyperparameterview.svelte
│ │ ├── KernelMathView.svelte
│ │ ├── PoolAnimator.svelte
│ │ ├── Poolview.svelte
│ │ └── Softmaxview.svelte
│ ├── main.js
│ ├── overview/
│ │ ├── Modal.svelte
│ │ ├── Overview.svelte
│ │ ├── draw-utils.js
│ │ ├── flatten-draw.js
│ │ ├── intermediate-draw.js
│ │ ├── intermediate-utils.js
│ │ └── overview-draw.js
│ ├── stores.js
│ └── utils/
│ ├── cnn-tf.js
│ ├── cnn.js
│ ├── deploy-to-gh-pages.sh
│ └── utlis.py
└── tiny-vgg/
├── README.md
├── environment.yaml
└── tiny-vgg.py
================================================
FILE CONTENTS
================================================
================================================
FILE: .github/workflows/build.yml
================================================
name: build
on:
# Triggers the workflow on push or pull request events but only for the master branch
push:
branches: [ master ]
pull_request:
branches: [ master ]
schedule:
- cron: "0 0 * * *"
jobs:
build:
runs-on: ${{ matrix.os }}
strategy:
matrix:
node-version: [16]
os: [ubuntu-latest, macos-latest, windows-latest]
steps:
- uses: actions/checkout@v3
- uses: actions/setup-node@v3
with:
node-version: ${{ matrix.node-version }}
- name: Install dependencies
run: npm install
- name: Build
run: npm run build
================================================
FILE: .gitignore
================================================
.DS_Store
node_modules
public/bundle.*
package-lock.json
public/assets/js/bundle.*
public/assets/js/
public/assets/css/bundle.*
*.swp
yarn.lock
dist/
local-build/
tiny-vgg/data/
pnpm-lock.yaml
================================================
FILE: LICENSE
================================================
MIT License
Copyright (c) 2020 Polo Club of Data Science
Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:
The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.
THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
================================================
FILE: README.md
================================================
# CNN Explainer
An interactive visualization system designed to help non-experts learn about Convolutional Neural Networks (CNNs)
[](https://github.com/poloclub/cnn-explainer/actions)
[](http://arxiv.org/abs/2004.15004)
[](https://doi.org/10.1109/TVCG.2020.3030418)
<a href="https://youtu.be/HnWIHWFbuUQ" target="_blank"><img src="https://i.imgur.com/sCsudVg.png" style="max-width:100%;"></a>
For more information, check out our manuscript:
[**CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization**](https://arxiv.org/abs/2004.15004).
Wang, Zijie J., Robert Turko, Omar Shaikh, Haekyu Park, Nilaksh Das, Fred Hohman, Minsuk Kahng, and Duen Horng Chau.
*IEEE Transactions on Visualization and Computer Graphics (TVCG), 2020.*
## Live Demo
For a live demo, visit: http://poloclub.github.io/cnn-explainer/
## Running Locally
Clone or download this repository:
```bash
git clone git@github.com:poloclub/cnn-explainer.git
# use degit if you don't want to download commit histories
degit poloclub/cnn-explainer
```
Install the dependencies:
```bash
npm install
```
Then run CNN Explainer:
```bash
npm run dev
```
Navigate to [localhost:3000](https://localhost:3000). You should see CNN Explainer running in your broswer :)
To see how we trained the CNN, visit the directory [`./tiny-vgg/`](tiny-vgg).
If you want to use CNN Explainer with your own CNN model or image classes, see [#8](/../../issues/8) and [#14](/../../issues/14).
## Credits
CNN Explainer was created by
<a href="https://zijie.wang/">Jay Wang</a>,
<a href="https://www.linkedin.com/in/robert-turko/">Robert Turko</a>,
<a href="http://oshaikh.com/">Omar Shaikh</a>,
<a href="https://haekyu.com/">Haekyu Park</a>,
<a href="http://nilakshdas.com/">Nilaksh Das</a>,
<a href="https://fredhohman.com/">Fred Hohman</a>,
<a href="http://minsuk.com">Minsuk Kahng</a>, and
<a href="https://www.cc.gatech.edu/~dchau/">Polo Chau</a>,
which was the result of a research collaboration between
Georgia Tech and Oregon State.
We thank
[Anmol Chhabria](https://www.linkedin.com/in/anmolchhabria),
[Kaan Sancak](https://kaansancak.com),
[Kantwon Rogers](https://www.kantwon.com), and the
[Georgia Tech Visualization Lab](http://vis.gatech.edu)
for their support and constructive feedback.
## Citation
```bibTeX
@article{wangCNNExplainerLearning2020,
title = {{{CNN Explainer}}: {{Learning Convolutional Neural Networks}} with {{Interactive Visualization}}},
shorttitle = {{{CNN Explainer}}},
author = {Wang, Zijie J. and Turko, Robert and Shaikh, Omar and Park, Haekyu and Das, Nilaksh and Hohman, Fred and Kahng, Minsuk and Chau, Duen Horng},
journal={IEEE Transactions on Visualization and Computer Graphics (TVCG)},
year={2020},
publisher={IEEE}
}
```
## License
The software is available under the [MIT License](https://github.com/poloclub/cnn-explainer/blob/master/LICENSE).
## Contact
If you have any questions, feel free to [open an issue](https://github.com/poloclub/cnn-explainer/issues/new/choose) or contact [Jay Wang](https://zijie.wang).
================================================
FILE: deploy-gh-page.sh
================================================
npm run build
cp -r ./public/assets ./dist
cp -r ./public/bundle* ./dist
cp -r ./public/global.css ./dist
npx gh-pages -m "Deploy $(git log '--format=format:%H' master -1)" -d ./dist
================================================
FILE: package.json
================================================
{
"name": "svelte-app",
"version": "1.0.0",
"devDependencies": {
"@rollup/plugin-replace": "^2.3.2",
"gh-pages": "^6.0.0",
"rollup": "^1.27.13",
"rollup-plugin-commonjs": "^10.0.0",
"rollup-plugin-livereload": "^1.0.0",
"rollup-plugin-node-resolve": "^5.2.0",
"rollup-plugin-svelte": "~6.1.1",
"rollup-plugin-terser": "^5.1.3",
"svelte": "^3.31.0"
},
"dependencies": {
"@tensorflow/tfjs": "^1.4.0",
"sirv-cli": "^0.4.4"
},
"scripts": {
"build": "rollup -c",
"dev": "rollup -c -w",
"start": "sirv public --single",
"start:dev": "sirv public --single --dev --port 3000",
"deploy": "npx"
}
}
================================================
FILE: public/assets/data/model.json
================================================
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================================================
FILE: public/assets/data/nn_10.json
================================================
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gitextract_939_80p5/
├── .github/
│ └── workflows/
│ └── build.yml
├── .gitignore
├── LICENSE
├── README.md
├── deploy-gh-page.sh
├── package.json
├── public/
│ ├── assets/
│ │ └── data/
│ │ ├── model.json
│ │ └── nn_10.json
│ ├── global.css
│ └── index.html
├── rollup.config.js
├── rollup_start_dev.js
├── src/
│ ├── App.svelte
│ ├── Explainer.svelte
│ ├── Header.svelte
│ ├── article/
│ │ ├── Article.svelte
│ │ └── Youtube.svelte
│ ├── config.js
│ ├── detail-view/
│ │ ├── ActivationAnimator.svelte
│ │ ├── Activationview.svelte
│ │ ├── ConvolutionAnimator.svelte
│ │ ├── Convolutionview.svelte
│ │ ├── Dataview.svelte
│ │ ├── DetailviewUtils.js
│ │ ├── HyperparameterAnimator.svelte
│ │ ├── HyperparameterDataview.svelte
│ │ ├── Hyperparameterview.svelte
│ │ ├── KernelMathView.svelte
│ │ ├── PoolAnimator.svelte
│ │ ├── Poolview.svelte
│ │ └── Softmaxview.svelte
│ ├── main.js
│ ├── overview/
│ │ ├── Modal.svelte
│ │ ├── Overview.svelte
│ │ ├── draw-utils.js
│ │ ├── flatten-draw.js
│ │ ├── intermediate-draw.js
│ │ ├── intermediate-utils.js
│ │ └── overview-draw.js
│ ├── stores.js
│ └── utils/
│ ├── cnn-tf.js
│ ├── cnn.js
│ ├── deploy-to-gh-pages.sh
│ └── utlis.py
└── tiny-vgg/
├── README.md
├── environment.yaml
└── tiny-vgg.py
SYMBOL INDEX (32 symbols across 6 files)
FILE: rollup_start_dev.js
method writeBundle (line 6) | writeBundle() {
FILE: src/detail-view/DetailviewUtils.js
function array1d (line 3) | function array1d(length, f) {
function array2d (line 7) | function array2d(height, width, f) {
function generateOutputMappings (line 11) | function generateOutputMappings(stride, output, kernelLength, padded_inp...
function compute_input_multiplies_with_weight (line 27) | function compute_input_multiplies_with_weight(hoverH, hoverW,
function getMatrixSliceFromInputHighlights (line 42) | function getMatrixSliceFromInputHighlights(matrix, highlights, kernelLen...
function getMatrixSliceFromOutputHighlights (line 50) | function getMatrixSliceFromOutputHighlights(matrix, highlights) {
function getVisualizationSizeConstraint (line 59) | function getVisualizationSizeConstraint(imageLength) {
function getDataRange (line 65) | function getDataRange(image) {
function gridData (line 78) | function gridData(image, constraint=getVisualizationSizeConstraint(image...
FILE: src/utils/cnn-tf.js
class Node (line 16) | class Node {
method constructor (line 26) | constructor(layerName, index, type, bias, output) {
class Link (line 39) | class Link {
method constructor (line 48) | constructor(source, dest, weight) {
FILE: src/utils/cnn.js
class Node (line 11) | class Node {
method constructor (line 21) | constructor(layerName, index, type, bias, output) {
class Link (line 34) | class Link {
method constructor (line 35) | constructor(source, dest, weight) {
FILE: src/utils/utlis.py
function convert_h5_to_json (line 7) | def convert_h5_to_json(model_h5_file, model_json_file):
FILE: tiny-vgg/tiny-vgg.py
function create_class_dict (line 17) | def create_class_dict():
function create_val_class_dict (line 36) | def create_val_class_dict():
function split_val_data (line 57) | def split_val_data():
function process_path_train (line 71) | def process_path_train(path):
function process_path_test (line 104) | def process_path_test(path):
function prepare_for_training (line 138) | def prepare_for_training(dataset, batch_size=32, cache=True,
function prepare_for_testing (line 157) | def prepare_for_testing(dataset, batch_size=32, cache=True):
class TinyVGG (line 171) | class TinyVGG(Model):
method __init__ (line 179) | def __init__(self, filters=10):
method call (line 196) | def call(self, x):
function train_step (line 220) | def train_step(image_batch, label_batch):
function vali_step (line 235) | def vali_step(image_batch, label_batch):
function test_step (line 244) | def test_step(image_batch, label_batch):
Condensed preview — 47 files, each showing path, character count, and a content snippet. Download the .json file or copy for the full structured content (693K chars).
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{
"path": "src/article/Article.svelte",
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"preview": "<script>\n\timport HyperparameterView from '../detail-view/Hyperparameterview.svelte';\n import Youtube from './Youtube.sv"
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"preview": "<script>\n export let data;\n export let highlights;\n export let outputLength;\n export let stride;\n export let paddin"
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"preview": "/* global d3, SmoothScroll */\n\nimport {\n svgStore, vSpaceAroundGapStore, hSpaceAroundGapStore, cnnStore,\n nodeCoordina"
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"preview": "/* global d3 */\n\nimport {\n svgStore, vSpaceAroundGapStore, hSpaceAroundGapStore, cnnStore,\n nodeCoordinateStore, selec"
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"chars": 8251,
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"path": "src/overview/overview-draw.js",
"chars": 30019,
"preview": "/* global d3, SmoothScroll */\n\nimport {\n svgStore, vSpaceAroundGapStore, hSpaceAroundGapStore, cnnStore,\n nodeCoordina"
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"path": "src/stores.js",
"chars": 937,
"preview": "import { writable } from 'svelte/store';\n\nexport const cnnStore = writable([]);\nexport const svgStore = writable(undefin"
},
{
"path": "src/utils/cnn-tf.js",
"chars": 15030,
"preview": "/* global tf */\n\n// Network input image size\nconst networkInputSize = 64;\n\n// Enum of node types\nconst nodeType = {\n IN"
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{
"path": "src/utils/cnn.js",
"chars": 15062,
"preview": "// Enum of node types\nconst nodeType = {\n INPUT: 'input',\n CONV: 'conv',\n POOL: 'pool',\n RELU: 'relu',\n FC: 'fc',\n "
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"path": "src/utils/deploy-to-gh-pages.sh",
"chars": 443,
"preview": "#!/bin/bash\nset -o errexit\n\n# config\ngit config --global user.email \"xiao.hk1997@gmail.com\"\ngit config --global user.nam"
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"path": "tiny-vgg/README.md",
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{
"path": "tiny-vgg/environment.yaml",
"chars": 250,
"preview": "name: tiny-vgg\nchannels:\n - defaults\ndependencies:\n - pip=20.0.2\n - python=3.6.10\n - pip:\n - h5py==2.10.0\n - n"
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{
"path": "tiny-vgg/tiny-vgg.py",
"chars": 12816,
"preview": "import tensorflow as tf\nimport numpy as np\nimport pandas as pd\nimport re\nfrom shutil import copyfile\nfrom glob import gl"
}
]
About this extraction
This page contains the full source code of the poloclub/cnn-explainer GitHub repository, extracted and formatted as plain text for AI agents and large language models (LLMs). The extraction includes 47 files (649.6 KB), approximately 185.8k tokens, and a symbol index with 32 extracted functions, classes, methods, constants, and types. Use this with OpenClaw, Claude, ChatGPT, Cursor, Windsurf, or any other AI tool that accepts text input. You can copy the full output to your clipboard or download it as a .txt file.
Extracted by GitExtract — free GitHub repo to text converter for AI. Built by Nikandr Surkov.