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Shape-Classifier

Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.

Clone

git clone "https://github.com/CSjianbel/Shape-Classifier.git"

Project Overview

  1. Generate the Data
    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network
    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model
    • 3 Modes:
      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify

Setup

pip install -r requirements.txt

Generate Images Data

python generate_shape_images.py

Train and Save a CNN model

python shape_classifier_model.py
python shape_classifier_model.py [model.h5]

Use the CNN model

Default model will be in Models/shape_classifier_model.h5.

python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]

Supported Shapes

  • Circles
  • Triangles
  • Squares
  • Rectangles

Contributing

Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.

License

MIT

A Project by Jiankarlo A. Belarmino

About

Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model

Topics

cnn-modelshape-classifier-model

Resources

Readme
MIT license
Activity

Stars

1 star

Watchers

1 watching

Forks

0 forks
Report repository

Releases

Packages

Contributors

Languages

, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
 blocks\n(function() {\n function addCopyButtons() {\n document.querySelectorAll('pre code').forEach(function(codeBlock) {\n if (codeBlock.parentElement.hasAttribute('data-copy-added')) return;\n codeBlock.parentElement.setAttribute('data-copy-added', 'true');\n \n var btn = document.createElement('button');\n btn.textContent = 'Copy';\n btn.style.cssText = 'position:absolute;top:4px;right:4px;padding:2px 8px;font-size:11px;background:#4ecdc4;border:none;border-radius:4px;color:#1a1a2e;cursor:pointer;opacity:0.7;transition:opacity 0.2s;';\n btn.onmouseover = function() { this.style.opacity = '1'; };\n btn.onmouseout = function() { this.style.opacity = '0.7'; };\n btn.onclick = function() {\n navigator.clipboard.writeText(codeBlock.textContent).then(function() {\n btn.textContent = 'Copied!';\n setTimeout(function() { btn.textContent = 'Copy'; }, 1500);\n });\n };\n codeBlock.parentElement.style.position = 'relative';\n codeBlock.parentElement.appendChild(btn);\n });\n }\n \n addCopyButtons();\n \n // Re-run on dynamic content\n var observer = new MutationObserver(addCopyButtons);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Add Copy Buttons to Code Blocks");
}
} catch(__e) { console.warn('[Userscript:Add Copy Buttons to Code Blocks]', __e); }
})();
(function(){
try {
var __m = "github.com";
var __re = new RegExp('^' + "github\\.com" + '

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Shape-Classifier
Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.
Clone
git clone "https://github.com/CSjianbel/Shape-Classifier.git"
Project Overview
  1. Generate the Data

    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network

    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model

    • 3 Modes:

      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify
Setup
pip install -r requirements.txt
Generate Images Data
python generate_shape_images.py
Train and Save a CNN model
python shape_classifier_model.py
python shape_classifier_model.py [model.h5]
Use the CNN model
Default model will be in Models/shape_classifier_model.h5.
python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]
Supported Shapes
  • Circles
  • Triangles
  • Squares
  • Rectangles
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
MIT
A Project by Jiankarlo A. Belarmino
About
Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model
Topics
cnn-modelshape-classifier-model
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Force GitHub README to respect dark mode\n(function() {\n var style = document.createElement('style');\n style.textContent = '\n .markdown-body {\n color-scheme: dark light;\n }\n .markdown-body pre { background: #161b22 !important; }\n .markdown-body code { background: rgba(110, 118, 129, 0.4) !important; }\n .markdown-body table th, .markdown-body table td { border-color: #30363d !important; }\n .markdown-body img { background: #0d1117; }\n .markdown-body blockquote { border-left-color: #8b949e; }\n .markdown-body hr { border-color: #30363d; }\n ';\n document.head.appendChild(style);\n})();", "GitHub Dark Mode README Fix");
}
} catch(__e) { console.warn('[Userscript:GitHub Dark Mode README Fix]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Repository files navigation
Shape-Classifier
Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.
Clone
git clone "https://github.com/CSjianbel/Shape-Classifier.git"
Project Overview
  1. Generate the Data

    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network

    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model

    • 3 Modes:

      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify
Setup
pip install -r requirements.txt
Generate Images Data
python generate_shape_images.py
Train and Save a CNN model
python shape_classifier_model.py
python shape_classifier_model.py [model.h5]
Use the CNN model
Default model will be in Models/shape_classifier_model.h5.
python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]
Supported Shapes
  • Circles
  • Triangles
  • Squares
  • Rectangles
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
MIT
A Project by Jiankarlo A. Belarmino
About
Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model
Topics
cnn-modelshape-classifier-model
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Highlight search terms from Google/DuckDuckGo/Bing referrer\n(function() {\n var ref = document.referrer;\n var terms = [];\n \n if (ref.includes('google.com') || ref.includes('duckduckgo.com') || ref.includes('bing.com')) {\n var url = new URL(ref);\n var q = url.searchParams.get('q') || url.searchParams.get('p');\n if (q) {\n terms = q.split(/\\s+/).filter(function(t) { return t.length > 2; });\n }\n }\n \n if (terms.length === 0) return;\n \n var style = document.createElement('style');\n style.textContent = '.userscript-highlight { background: #fbbf24; color: #1a1a2e; padding: 1px 3px; border-radius: 2px; }';\n document.head.appendChild(style);\n \n function highlight(node) {\n if (node.nodeType === 3) { // text node\n var text = node.textContent;\n var found = false;\n terms.forEach(function(term) {\n var regex = new RegExp('(' + term.replace(/[.*+?^${}()|[\\]\\\\]/g, '\\\\') + ')', 'gi');\n if (regex.test(text)) {\n found = true;\n var frag = document.createDocumentFragment();\n var parts = text.split(regex);\n parts.forEach(function(part, i) {\n if (i % 2 === 0) {\n frag.appendChild(document.createTextNode(part));\n } else {\n var span = document.createElement('span');\n span.className = 'userscript-highlight';\n span.textContent = part;\n frag.appendChild(span);\n }\n });\n node.parentNode.replaceChild(frag, node);\n }\n });\n } else if (node.nodeType === 1 && node.childNodes) { // element\n var skipTags = ['SCRIPT', 'STYLE', 'NOSCRIPT', 'TEXTAREA', 'INPUT', 'SELECT'];\n if (!skipTags.includes(node.tagName)) {\n Array.from(node.childNodes).forEach(highlight);\n }\n }\n }\n \n highlight(document.body);\n \n // Re-highlight on dynamic content\n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1 || node.nodeType === 3) highlight(node);\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Highlight Search Terms");
}
} catch(__e) { console.warn('[Userscript:Highlight Search Terms]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Repository files navigation
Shape-Classifier
Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.
Clone
git clone "https://github.com/CSjianbel/Shape-Classifier.git"
Project Overview
  1. Generate the Data

    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network

    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model

    • 3 Modes:

      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify
Setup
pip install -r requirements.txt
Generate Images Data
python generate_shape_images.py
Train and Save a CNN model
python shape_classifier_model.py
python shape_classifier_model.py [model.h5]
Use the CNN model
Default model will be in Models/shape_classifier_model.h5.
python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]
Supported Shapes
  • Circles
  • Triangles
  • Squares
  • Rectangles
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
MIT
A Project by Jiankarlo A. Belarmino
About
Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model
Topics
cnn-modelshape-classifier-model
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Strip utm_, fbclid, gclid, etc. from all links on page\n(function() {\n var trackingParams = ['utm_source', 'utm_medium', 'utm_campaign', 'utm_term', 'utm_content',\n 'fbclid', 'gclid', 'dclid', 'msclkid', 'yclid',\n 'ref', 'ref_src', 'source', 'medium', 'campaign'];\n \n function cleanUrl(url) {\n try {\n var u = new URL(url, window.location.origin);\n var changed = false;\n trackingParams.forEach(function(p) {\n if (u.searchParams.has(p)) {\n u.searchParams.delete(p);\n changed = true;\n }\n });\n return changed ? u.toString() : url;\n } catch (e) {\n return url;\n }\n }\n \n function cleanLinks() {\n document.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n \n cleanLinks();\n \n var observer = new MutationObserver(function(mutations) {\n mutations.forEach(function(m) {\n m.addedNodes.forEach(function(node) {\n if (node.nodeType === 1) {\n if (node.tagName === 'A') cleanLinks();\n node.querySelectorAll('a[href]').forEach(function(a) {\n var clean = cleanUrl(a.href);\n if (clean !== a.href) a.href = clean;\n });\n }\n });\n });\n });\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "Remove Tracking Parameters from Links");
}
} catch(__e) { console.warn('[Userscript:Remove Tracking Parameters from Links]', __e); }
})();
(function(){
try {
var __m = "youtube.com";
var __re = new RegExp('^' + "youtube\\.com" + '

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Repository files navigation
Shape-Classifier
Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.
Clone
git clone "https://github.com/CSjianbel/Shape-Classifier.git"
Project Overview
  1. Generate the Data

    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network

    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model

    • 3 Modes:

      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify
Setup
pip install -r requirements.txt
Generate Images Data
python generate_shape_images.py
Train and Save a CNN model
python shape_classifier_model.py
python shape_classifier_model.py [model.h5]
Use the CNN model
Default model will be in Models/shape_classifier_model.h5.
python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]
Supported Shapes
  • Circles
  • Triangles
  • Squares
  • Rectangles
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
MIT
A Project by Jiankarlo A. Belarmino
About
Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model
Topics
cnn-modelshape-classifier-model
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Auto-enable theater mode on YouTube\n(function() {\n function tryTheater() {\n var btn = document.querySelector('button[aria-label=\"Theater mode\"], ytd-player #player button[title=\"Theater mode\"]');\n if (btn && !btn.classList.contains('activated')) {\n btn.click();\n }\n }\n \n // Try immediately\n tryTheater();\n \n // Try after navigation (SPA)\n var lastUrl = location.href;\n setInterval(function() {\n if (location.href !== lastUrl) {\n lastUrl = location.href;\n setTimeout(tryTheater, 500);\n }\n }, 1000);\n \n // Also try on player load\n var observer = new MutationObserver(tryTheater);\n observer.observe(document.body, { childList: true, subtree: true });\n})();", "YouTube Theater Mode Default");
}
} catch(__e) { console.warn('[Userscript:YouTube Theater Mode Default]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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Repository files navigation
Shape-Classifier
Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.
Clone
git clone "https://github.com/CSjianbel/Shape-Classifier.git"
Project Overview
  1. Generate the Data

    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network

    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model

    • 3 Modes:

      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify
Setup
pip install -r requirements.txt
Generate Images Data
python generate_shape_images.py
Train and Save a CNN model
python shape_classifier_model.py
python shape_classifier_model.py [model.h5]
Use the CNN model
Default model will be in Models/shape_classifier_model.h5.
python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]
Supported Shapes
  • Circles
  • Triangles
  • Squares
  • Rectangles
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
MIT
A Project by Jiankarlo A. Belarmino
About
Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model
Topics
cnn-modelshape-classifier-model
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Remove or un-stick sticky/fixed headers that block content\n(function() {\n function unstick() {\n document.querySelectorAll('header, nav, [role=\"banner\"], .header, .navbar, .sticky, .fixed-top, [style*=\"position: fixed\"], [style*=\"position:sticky\"]').forEach(function(el) {\n if (el.style.position === 'fixed' || el.style.position === 'sticky' || \n getComputedStyle(el).position === 'fixed' || getComputedStyle(el).position === 'sticky') {\n el.style.position = 'static';\n el.style.top = 'auto';\n el.style.zIndex = 'auto';\n }\n });\n }\n \n unstick();\n \n var observer = new MutationObserver(unstick);\n observer.observe(document.body, { childList: true, subtree: true, attributes: true, attributeFilter: ['style', 'class'] });\n})();", "Kill Sticky Headers");
}
} catch(__e) { console.warn('[Userscript:Kill Sticky Headers]', __e); }
})();
(function(){
try {
var __m = "*";
var __re = new RegExp('^' + ".*" + '

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12 Commits
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Repository files navigation
Shape-Classifier
Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.
Clone
git clone "https://github.com/CSjianbel/Shape-Classifier.git"
Project Overview
  1. Generate the Data

    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network

    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model

    • 3 Modes:

      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify
Setup
pip install -r requirements.txt
Generate Images Data
python generate_shape_images.py
Train and Save a CNN model
python shape_classifier_model.py
python shape_classifier_model.py [model.h5]
Use the CNN model
Default model will be in Models/shape_classifier_model.h5.
python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]
Supported Shapes
  • Circles
  • Triangles
  • Squares
  • Rectangles
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
MIT
A Project by Jiankarlo A. Belarmino
About
Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model
Topics
cnn-modelshape-classifier-model
Resources
Readme
MIT license
Activity
Stars
1 star
Watchers
1 watching
Forks
0 forks
Report repository
Releases
Packages
Contributors
Languages

, 'i');
if (__m === '*' || __re.test(location.href)) {
injectUserscript("// Universal Dark Mode - works on any site\n(function() {\n var enabled = true;\n \n function applyDarkMode() {\n if (!enabled) return;\n \n // Create style element if it doesn't exist\n var style = document.getElementById('universal-dark-mode-style');\n if (!style) {\n style = document.createElement('style');\n style.id = 'universal-dark-mode-style';\n document.head.appendChild(style);\n }\n \n // Dark mode CSS - inverts colors but preserves images/video\n style.textContent = '\n /* Invert everything except media */\n html {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #1a1a2e !important;\n }\n \n /* Restore images, videos, iframes, canvas */\n img, video, iframe, canvas, svg, picture, [style*=\"background-image\"] {\n filter: invert(1) hue-rotate(180deg) !important;\n }\n \n /* Preserve specific elements that should not be inverted */\n .no-dark-mode, .no-dark-mode *,\n [data-theme=\"light\"], [data-theme=\"light\"],\n .ace_editor, .ace_editor *,\n .CodeMirror, .CodeMirror *,\n .monaco-editor, .monaco-editor *,\n .markdown-body pre, .markdown-body pre *,\n .highlight, .highlight *,\n pre code, pre code * {\n filter: none !important;\n }\n \n /* Fix common UI elements */\n .modal, .popup, .dropdown-menu, .tooltip, .popover {\n filter: invert(1) hue-rotate(180deg) !important;\n background: #2d2d44 !important;\n border-color: #444 !important;\n }\n \n /* Scrollbars */\n ::-webkit-scrollbar { background: #1a1a2e !important; }\n ::-webkit-scrollbar-thumb { background: #444 !important; }\n ::-webkit-scrollbar-thumb:hover { background: #555 !important; }\n \n /* Selection */\n ::selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ::-moz-selection { background: #4ecdc4 !important; color: #1a1a2e !important; }\n ';\n }\n \n function removeDarkMode() {\n var style = document.getElementById('universal-dark-mode-style');\n if (style) style.remove();\n }\n \n // Toggle with Alt+Shift+D\n document.addEventListener('keydown', function(e) {\n if (e.altKey && e.shiftKey && e.key === 'D') {\n e.preventDefault();\n enabled = !enabled;\n if (enabled) {\n applyDarkMode();\n console.log('[Universal Dark Mode] Enabled');\n } else {\n removeDarkMode();\n console.log('[Universal Dark Mode] Disabled');\n }\n }\n });\n \n // Apply on load\n applyDarkMode();\n \n // Re-apply on dynamic content\n var observer = new MutationObserver(function(mutations) {\n if (enabled && !document.getElementById('universal-dark-mode-style')) {\n applyDarkMode();\n }\n });\n observer.observe(document.head, { childList: true });\n \n console.log('[Universal Dark Mode] Loaded - Press Alt+Shift+D to toggle');\n})();", "Universal Dark Mode");
}
} catch(__e) { console.warn('[Userscript:Universal Dark Mode]', __e); }
})();
})();

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Repository files navigation
Shape-Classifier
Machine Learning Model that accurately classifies shapes such as circles, triangles, squares and rectangles.
Clone
git clone "https://github.com/CSjianbel/Shape-Classifier.git"
Project Overview
  1. Generate the Data

    • Generate n random images of shapes
  2. Create and train a Convolutional Neural Network

    • Load in the dataset
    • Feed into the CNN
    • Make Tweaks on CNN model to improve accuracy/performance
  3. Python Application that utilizes the shape classifier model

    • 3 Modes:

      1. User provides image to be classified
      2. GUI application that let's the user draw shapes and the model classifies the drawing
      3. Webcam, the user can turn on their camera and show hand-drawn shapes to the camera for the model to classify
Setup
pip install -r requirements.txt
Generate Images Data
python generate_shape_images.py
Train and Save a CNN model
python shape_classifier_model.py
python shape_classifier_model.py [model.h5]
Use the CNN model
Default model will be in Models/shape_classifier_model.h5.
python shape_classifier.py
python shape_classifier.py --webcam
python shape_classifier.py [path to image]
python shape_classifer.py -m [path to model]
Supported Shapes
  • Circles
  • Triangles
  • Squares
  • Rectangles
Contributing
Pull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
License
MIT
A Project by Jiankarlo A. Belarmino
About
Creates a dataset, learns to classify shapes using the generated dataset and a GUI app that uses the trained Shape Classifier Model
Topics
cnn-modelshape-classifier-model
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MIT license
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