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* Adds face-api demos (#161) * added face-expressions demo * added classifyExpressionsMultiple * rm model files and model path requirement * added face landmarks example * clean up example * rm options in example * added local models example * changed function names * updated examples to use .detect() * rm translation * added image example of Frida * added detectSingle * updated image landmarks with landmarks.parts * refactored code friendly and changed colors * made ex friendly * changed options from withFaceX to withX * Structure examples directories for consistency (#170) * moved CVAE example to dir * moved dcgan to random for random space * moved sentiment to dir * moved word2vec to dir * moved files * rm p5 lib * match javascript example folder structure * Examples index page (#171) * added placeholder index.html and node script * adds ml5 index page * added latent vector example (#175) * Trying out some new example ideas for DCGAN latent vector * added simpler demo (#181) * moved index.html to /public (#182) * [In progress] Support for p5 Instance mode in ml5.js example (#160) * added bodypix_p5Instance * adds p5Instance mode example * [in progress] Adds plain javascript examples based on the p5 examples (#165) * added plain js bodypix examples * added cvae example * added dcgan example * added faceapi with landmarks // todo expressions * stashing changes for now * moved files * added yolo webcam plain js * added yolo image example * remove text on p5 * rm p5 scripts * adds bodyPix examples * wip expressions demo * adds faceapi expressions demo * adds charRNN_interactive example * added charRNN_test * added charRnn_text_stateful' * adds ImageClassification_Video_Load * added ImageClassification_DoodleNet_Canvas * added sentiment ex * adds unet example * add doodlenet_video - NOT WORKING * added posenet examples - NOT WORKING * added posenet_image_single * adds part selection example - NEEDS REVIEW * adds examples for posnet * added styletransfer video plainjs * added word2vec example * rm p5 ref * added sketchRnn basic example * added sketchRnn interactive * adds pix2pix example * add pix2pix promise * adds speech command * adds speech commands example * adds plain js pitchDetection * adds pitch game * format text * adds knn video example * adds knn classifier video example * adds knn classifier posenet * adds regressor fe * adds videosquare * adds sound example * adds piano ex * adds scavenger hunt - works only in chrome for now * adds video and sound example * adds doodlenet examples * adds multiple example * update bodypix examples * update cvae * adds updates to faceapi and dcgan * updates yolo * updats examples * adds teachable machine image classification example (#196) * rm expressions references in faceapi examples (#202) * adds live-server to npm scripts (#204) * update gh templates (#211) * Generic Neural Net Example (#164) * added example * added co2 net - WORK IN PROGRESS * updated model and loaded data from model * fix unNormalize * refactored code * added axes * added axes * added message about log transform * added legend in html * adds placeholder for titanic example * adds data, constructor, and laodData * adds normalize data function * adds training function * updates example * adds neural network training * Speculative Ideas about Titanic Example (#187) * speculative ideas with example * since it's classification is there a way to mirror other ml5 classification examples? * refactor of titanic example * Adds titanic example to match diy-nn-with-data (#188) * adds experimental csv and specified string as output * working with titanic * update examples - TODO: feed in normalized vals for titanic inputs * adds simple regression example placeholder * adds simple regression example * comments train with options * moves batchSize and epoch options * change to .classify() * updates co2 training sketch with predict vals from 0 - 1 * update to classify * updates basic -- broken * changes inputs and fixes undef. * changes data in basic * whitespace adjustments * some cleanup and ideas for titanic example * speculative port of color classifier example * rm shuffle() * updates color classifier example * change vals to arrays in .addData() * work on neural network color classifier (#190) * small adjustments for testing code with ml5js/ml5-library#574 * example cleanup todos * updates color classifier example to reflect current generic nn * Updating Titanic Example (#191) * redoing titanic example with final cleaned data from @lydiajessup * training is working but issue with predict and passing in strings * working with manually encoding of inputs to predict() * updates titanic sketch * porting tf.js XOR example from coding train challenge (#192) * porting tf.js XOR example from coding train challenge * adding learning rate * noting hiddenUnits variable * updating color classifier see: ml5js/ml5-library#581 * refactor titanic example * using label directly * logs not loss * trying values * moving sketch.js * update simple regression * updates regression sketch * update co2 example * update to use results.outputs * Refactors examples to match diy-nn-refactor branch (#195) * neural noteplayer example * example inspired by Eyeo 2019 Rebecca Fiebrink talk * rename musical mouse example * example tweaks and oscillator * adds refactoring examples * updates examples based in refactor * updates xor" * rm unused co2net * updates examples for regression * updates musical note example * adds experimental normalizationOptions * adds example of multi layered network * changes activations * adds simple classification example * changes .normalize() to .normalizeData() * updates all examples to handle array of .predict() or .classify() output * Pass over DIY interactive data examples (#198) * neural noteplayer example * example inspired by Eyeo 2019 Rebecca Fiebrink talk * rename musical mouse example * example tweaks and oscillator * musical face example * different interface for face example * mouse and pixels cleanup * musical face adjust to new API * code comments * low res pixel comments and naming * Clean-up of interactive neural network examples (#201) * neural noteplayer example * example inspired by Eyeo 2019 Rebecca Fiebrink talk * rename musical mouse example * example tweaks and oscillator * musical face example * different interface for face example * mouse and pixels cleanup * musical face adjust to new API * code comments * low res pixel comments and naming * comments and cleanup for face example * normalize automatically face * DIY Neural Network mouseXY classification example (#199) * neural noteplayer example * example inspired by Eyeo 2019 Rebecca Fiebrink talk * rename musical mouse example * example tweaks and oscillator * musical face example * different interface for face example * mouse and pixels cleanup * musical face adjust to new API * code comments * attempting DIY classification example * ? * fixes outputs and changes function to .classify() * posenet classification example * rm console.log * rm withExpressions in musical face * [diy nn] Updates examples to use labels for inputs/outputs (#205) * updates musical mouse and xy classifier with specific input/output labels * update titles * update text in co2net * adds load data function (#206) * adds xOR example with multiPredict (#207) * [WIP] DIY NN - examples for loading model (#210) * adds loadModel example * updates example showcasing issues * updated example to reflect current ml5-lib temp fix * Updates model_load example (#212) * adds loadModel example * updates example showcasing issues * updated example to reflect current ml5-lib temp fix * updates loading model example * rm faceapi examples with expressions (#213) * Updates bodypix examples to use preload() for p5js examples (#214) * adds preload example * updates bodypix to use preload() * Kmeans Image Segmentation Example (#215) * adds simple kmeans clustering example * code cleanup * change image size to 30 x 30 to run faster * changes ml5 version to 0.4.0 * updates public index * updates ml5 version and updater script * update npm script name" * adds 2019 * updates p5 to version 0.9.0 * sets localhost * Revising Teachable Machine Snippets (#218) * matching proposed TM snippets for image classification * sound example and refactoring to new TM folder * changing name to include URL * fix typo * adds flipped video (#219) * updates bodypix examples to reflect updated api (#225) * adds p5 batch uploader script * adds p5 batch uploader script (#227) * set ml to dev * adds background to unet * bumps version
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GITHUB_ID=<add your info here> | ||
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ML5_EXAMPLES_USERNAME=ml5 | ||
EDITOR_API_ACCESS_TOKEN=<p5 web editor access token> | ||
EDITOR_API_URL=https://editor.p5js.org/api/v1 |
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<title>ml5.js kmeans example</title> | ||
<script src="https://d3js.org/d3.v4.min.js"></script> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<title>BodyPix with Webcam</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<meta charset="UTF-8"> | ||
<title>BodyPix with Webcam</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>BodyPix with Webcam</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<title>CVAE with quick_draw</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<meta charset="UTF-8"> | ||
<title>Interactive CharRNN Text Generation Example</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<h2>This example uses a pre-trained model on a corpus of <a href="https://en.wikipedia.org/wiki/Virginia_Woolf">Virginia Woolf</a></h2> | ||
<textarea id="textInput" style="width: 300px; height: 50px;" placeholder="type here"></textarea> | ||
<br /> length: | ||
<input id="lenSlider" type="range" min="1" max="100" value="20" /> <span id="length">20</span> | ||
<input id="lenSlider" type="range" min="1" max="100" value="20" /> <span id="length">20</span> | ||
<br /> temperature: | ||
<input id="tempSlider" type="range" min="0" max="1" step="0.01" /><span id="temperature">0.5</span> | ||
<input id="tempSlider" type="range" min="0" max="1" step="0.01" /><span id="temperature">0.5</span> | ||
<p id="status">Loading Model</p> | ||
<p id="result"> | ||
<span id="original"></span><span id="prediction"></span> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>LSTM Text Generation Example</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<h1>LSTM Text Generation Example</h1> | ||
<h2>This example uses a pre-trained model on a corpus of <a href="https://en.wikipedia.org/wiki/Virginia_Woolf">Virginia Woolf</a></h2> | ||
<p>seed text: | ||
<input id="textInput" value="The meaning of life is" /> | ||
<input id="textInput" value="The meaning of life is" /> | ||
</p> | ||
<p>length: | ||
<input id="lenSlider" type="range" min="10" max="500" value="100" /> <span id="length">100</span></p> | ||
<input id="lenSlider" type="range" min="10" max="500" value="100" /> <span id="length">100</span></p> | ||
<p>temperature: | ||
<input id="tempSlider" type="range" min="0" max="1" step="0.01" /><span id="temperature">0.5</span></p> | ||
<input id="tempSlider" type="range" min="0" max="1" step="0.01" /><span id="temperature">0.5</span></p> | ||
<p id="status">Loading Model</p> | ||
<button id="generate">generate</button> | ||
<p id="result"></p> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>Stateful CharRNN Text Generation Example</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<p>Instead of feeding every single character every frame to predict the next character, we feed only the last character, and instruct the CharRNN to remember its internal state.</p> | ||
<p>This example uses a pre-trained model on a corpus of <a href="https://en.wikipedia.org/wiki/Virginia_Woolf">Virginia Woolf</a></p> | ||
<p>seed text: | ||
<input id="textInput" value="The sky was blue and " /> | ||
<input id="textInput" value="The sky was blue and " /> | ||
</p> | ||
<p>temperature: | ||
<input id="tempSlider" type="range" min="0" max="1" step="0.01" /><span id="temperature">0.5</span> | ||
<input id="tempSlider" type="range" min="0" max="1" step="0.01" /><span id="temperature">0.5</span> | ||
</p> | ||
<p><button id="reset">Reset</button><button id="start">Start</button><button id="single">Single</button></p> | ||
<p id="status">Loading Model</p> | ||
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<meta name="viewport" content="width=device-width, initial-scale=1"> | ||
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<title>DCGAN Example</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="sketch.js"></script> | ||
</head> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>FaceApi Landmarks Demo</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>FaceApi Landmarks Demo</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<meta charset="UTF-8"> | ||
<title>FaceApi Landmarks Demo With Local Models</title> | ||
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<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<title>Image Classification using Feature Extraction with MobileNet</title> | ||
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<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<meta charset="UTF-8"> | ||
<title>Image Regression using Feature Extraction with MobileNet.</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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</div> | ||
<h6><span id="modelStatus">Loading base model...</span> | <span id="videoStatus">Loading video...</span></h6> | ||
<p> | ||
<input type="range" name="slider" id="slider" min="0.01" max="1.0" step="0.01" value="0.5" /> | ||
<input type="range" name="slider" id="slider" min="0.01" max="1.0" step="0.01" value="0.5" /> | ||
</p> | ||
<br /> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>Image Classification Example</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<h1>Image classification using MobileNet</h1> | ||
<p>The MobileNet model labeled this as <span id="result">...</span> with a confidence of <span id="probability">...</span>.</p> | ||
<img src="images/bird.jpg" id="image" width="400" /> | ||
<img src="images/bird.jpg" id="image" width="400" /> | ||
<script src="sketch.js"></script> | ||
</body> | ||
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<title>Canvas Image Classification using DoodleNet</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<title>Webcam Image Classification using DoodleNet</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<meta charset="UTF-8"> | ||
<title>Multiple Image classification using MobileNet</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<title>Webcam Image Classification using MobileNet</title> | ||
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<title>Webcam Image Classification with Speech Output using MobileNet</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<title>Webcam Image Classification with Speech Output using MobileNet</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>Webcam Image Classification using a pre-trianed customized model</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
</head> | ||
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<body> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>PoseNet with KNN Classification on Webcam Images</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<style></style> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>KNN Classification on Webcam Images with mobileNet.</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<style></style> | ||
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<title>KNN Classification on Webcam Images with Speech Output Using mobileNet.</title> | ||
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<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<style></style> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>KNN Classification on Webcam Images with mobileNet</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<style></style> | ||
</head> | ||
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<meta charset="UTF-8"> | ||
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<title>Pitch Detection</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>Pitch Tone Game</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<meta charset="UTF-8"> | ||
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<title>Pitch Detect Piano</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>Pix2Pix Edges2Pikachu Example</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<p>4. You could click the "Clear" button to clear the canvas and draw again.</p> | ||
<p id="status">Loading Model... Please wait...</p> | ||
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<img id="inputImage" width="256px" src="images/input.png" alt="input image" /> | ||
<img id="outputImage" width="256px" src="" alt="output image" /> | ||
<img id="inputImage" width="256px" src="images/input.png" alt="input image" /> | ||
<img id="outputImage" width="256px" src="" alt="output image" /> | ||
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<div class="flex"> | ||
<div> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>Pix2Pix Edges2Pikachu Example</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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<style></style> | ||
</head> | ||
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<p>4. You could click the "Clear" button to clear the canvas and draw again.</p> | ||
<p id="status">Loading Model... Please wait...</p> | ||
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<img id="inputImage" width="256px" src="images/input.png" alt="input image" /> | ||
<img id="outputImage" width="256px" src="" alt="output image" /> | ||
<img id="inputImage" width="256px" src="images/input.png" alt="input image" /> | ||
<img id="outputImage" width="256px" src="" alt="output image" /> | ||
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<div class="flex"> | ||
<div> | ||
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<head> | ||
<meta charset="UTF-8"> | ||
<title>PoseNet example on image with single detection</title> | ||
<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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</head> | ||
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<body> | ||
<h1>PoseNet example on image with single detection</h1> | ||
<p id='status'>Loading model...</p> | ||
<img id="image" style="display:none" src="data/runner.jpg" alt="runner image" /> | ||
<img id="image" style="display:none" src="data/runner.jpg" alt="runner image" /> | ||
<canvas id="canvas"></canvas> | ||
<p>image via: <a href="https://www.pexels.com/photo/topless-man-wearing-grey-and-black-shorts-sprinting-on-concrete-road-1401796/" target="_blank">Pexels</a></p> | ||
<script src="sketch.js"></script> | ||
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<meta charset="UTF-8"> | ||
<title>PoseNet Part Selection</title> | ||
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<script src="https://unpkg.com/[email protected].1/dist/ml5.min.js" type="text/javascript"></script> | ||
<script src="https://unpkg.com/[email protected].2/dist/ml5.min.js" type="text/javascript"></script> | ||
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</head> | ||
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