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SpotCheckAI

Introduction

SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.

SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.

SpotCheckAI's Webpage

Installation Guide

Front End

Available on the web at: [insert website link here]

To Install Locally:

  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve

Note: Port is to localhost 8000

Back End

Available on the web at: [insert website link here]

Note: Interface is not interactable on web-hosted website.

To Install Locally:

  1. Clone Repository

  2. Create Virtual Environment

  3. Install dependencies

pip install -r /path/to/requirements.txt
  1. cd path/to/backend/folder
  2. python manage.py runserver 7000

Note: Port is to localhost 7000

Folders

  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application

About

Leung, Rafferty - Spring 2023 Online

Resources

Readme
Activity

Stars

2 stars

Watchers

1 watching

Forks

2 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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SpotCheckAI
Introduction
SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.
SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.
SpotCheckAI's Webpage
Installation Guide
Front End
Available on the web at: [insert website link here]
To Install Locally:
  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve
Note: Port is to localhost 8000
Back End
Available on the web at: [insert website link here]
Note: Interface is not interactable on web-hosted website.
To Install Locally:
  1. Clone Repository
  2. Create Virtual Environment
  3. Install dependencies
pip install -r /path/to/requirements.txt

  1. cd path/to/backend/folder
  2. python manage.py runserver 7000
Note: Port is to localhost 7000
Folders
  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application
About
Leung, Rafferty - Spring 2023 Online
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
2 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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BranchesTags
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SpotCheckAI
Introduction
SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.
SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.
SpotCheckAI's Webpage
Installation Guide
Front End
Available on the web at: [insert website link here]
To Install Locally:
  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve
Note: Port is to localhost 8000
Back End
Available on the web at: [insert website link here]
Note: Interface is not interactable on web-hosted website.
To Install Locally:
  1. Clone Repository
  2. Create Virtual Environment
  3. Install dependencies
pip install -r /path/to/requirements.txt

  1. cd path/to/backend/folder
  2. python manage.py runserver 7000
Note: Port is to localhost 7000
Folders
  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application
About
Leung, Rafferty - Spring 2023 Online
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
2 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('^' + ".*" + '

Skip to content
BranchesTags
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SpotCheckAI
Introduction
SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.
SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.
SpotCheckAI's Webpage
Installation Guide
Front End
Available on the web at: [insert website link here]
To Install Locally:
  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve
Note: Port is to localhost 8000
Back End
Available on the web at: [insert website link here]
Note: Interface is not interactable on web-hosted website.
To Install Locally:
  1. Clone Repository
  2. Create Virtual Environment
  3. Install dependencies
pip install -r /path/to/requirements.txt

  1. cd path/to/backend/folder
  2. python manage.py runserver 7000
Note: Port is to localhost 7000
Folders
  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application
About
Leung, Rafferty - Spring 2023 Online
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
2 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" + '

Skip to content
BranchesTags
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SpotCheckAI
Introduction
SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.
SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.
SpotCheckAI's Webpage
Installation Guide
Front End
Available on the web at: [insert website link here]
To Install Locally:
  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve
Note: Port is to localhost 8000
Back End
Available on the web at: [insert website link here]
Note: Interface is not interactable on web-hosted website.
To Install Locally:
  1. Clone Repository
  2. Create Virtual Environment
  3. Install dependencies
pip install -r /path/to/requirements.txt

  1. cd path/to/backend/folder
  2. python manage.py runserver 7000
Note: Port is to localhost 7000
Folders
  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application
About
Leung, Rafferty - Spring 2023 Online
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
2 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('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
SpotCheckAI
Introduction
SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.
SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.
SpotCheckAI's Webpage
Installation Guide
Front End
Available on the web at: [insert website link here]
To Install Locally:
  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve
Note: Port is to localhost 8000
Back End
Available on the web at: [insert website link here]
Note: Interface is not interactable on web-hosted website.
To Install Locally:
  1. Clone Repository
  2. Create Virtual Environment
  3. Install dependencies
pip install -r /path/to/requirements.txt

  1. cd path/to/backend/folder
  2. python manage.py runserver 7000
Note: Port is to localhost 7000
Folders
  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application
About
Leung, Rafferty - Spring 2023 Online
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
2 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('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
SpotCheckAI
Introduction
SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.
SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.
SpotCheckAI's Webpage
Installation Guide
Front End
Available on the web at: [insert website link here]
To Install Locally:
  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve
Note: Port is to localhost 8000
Back End
Available on the web at: [insert website link here]
Note: Interface is not interactable on web-hosted website.
To Install Locally:
  1. Clone Repository
  2. Create Virtual Environment
  3. Install dependencies
pip install -r /path/to/requirements.txt

  1. cd path/to/backend/folder
  2. python manage.py runserver 7000
Note: Port is to localhost 7000
Folders
  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application
About
Leung, Rafferty - Spring 2023 Online
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
2 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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SpotCheckAI
Introduction
SpotCheckAI is a full-stack progressive web application (PWA) that can identify suspicious skin lesions as benign or cancerous. Users upload an image to the website and based on the Convolutional Neural Network Model, it will give a percentage of certainty that the model thinks is cancerous or benign.
SpotCheckAI's chatbot is powered by OpenAI's GPT-3 model and can answer questions regarding the results received or the website.
SpotCheckAI's Webpage
Installation Guide
Front End
Available on the web at: [insert website link here]
To Install Locally:
  1. Clone Repository
  2. cd path/to/frontend/folder
  3. ionic serve
Note: Port is to localhost 8000
Back End
Available on the web at: [insert website link here]
Note: Interface is not interactable on web-hosted website.
To Install Locally:
  1. Clone Repository
  2. Create Virtual Environment
  3. Install dependencies
pip install -r /path/to/requirements.txt

  1. cd path/to/backend/folder
  2. python manage.py runserver 7000
Note: Port is to localhost 7000
Folders
  1. backend: contains all the files pertaining to the backend application
  2. data: data used to train the ML model
  3. documents: archive of documents
  4. frontend-website: contains all the files pertaining to the frontend webpage
  5. got-web-crawl-qa: contains webscraper and embeddings for the chatbot
  6. model development: development of ML model
  7. models: contains the ML model used in the application
About
Leung, Rafferty - Spring 2023 Online
Resources
Readme
Activity
Stars
2 stars
Watchers
1 watching
Forks
2 forks
Report repository
Releases
Packages
Contributors
Languages