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Repository files navigation

Project Name: GeoGuard

Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.

Video Demonstration:

GeoGuard.2024.mp4

Techstack:

  • Frontend:

    • Powered by React
    • Integrated with Google Maps API

  • Database:

    • Managed using Firebase

  • Backend:

    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics

  • Hosting:

    • Hosted on Google App Engine
    • Load balancer included for optimal performance

How to Setup Locally

Setup ML Model

💻 Install

#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt

📸 Execute

python3 -m main

Setup Dashboard

💻 Install

# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install

📸 Execute

#Run servercd server
npm start
#on a separate cmd Run client
npm start

Modules

1. Camera Registration Module:

  • Enrollment of cameras and data storage.
  • Administration of geotagged data.

2. Module for Geotagging:

  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.

3. Object Detection and failure detection:

  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.

4. Alerting:

  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.

5. Command and Control Center Module:

  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.

Goals to achieve

  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques

Achievements

  • Qualified for preliminary round of IEEE YESIST12.

  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)

  • Presented project idea for City institute of disaster Management(BMC)

About

No description, website, or topics provided.

Resources

Readme
Activity

Stars

3 stars

Watchers

1 watching

Forks

4 forks
Report repository

Releases

Packages

Used by

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" + '

Skip to content
BranchesTags
Repository files navigation
Project Name: GeoGuard
Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.
Video Demonstration:
GeoGuard.2024.mp4
Techstack:
  • Frontend:
    • Powered by React
    • Integrated with Google Maps API
  • Database:
    • Managed using Firebase
  • Backend:
    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics
  • Hosting:
    • Hosted on Google App Engine
    • Load balancer included for optimal performance
How to Setup Locally
Setup ML Model
💻 Install
#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt
📸 Execute
python3 -m main
Setup Dashboard
💻 Install
# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install
📸 Execute
#Run servercd server
npm start
#on a separate cmd Run client
npm start
Modules
1. Camera Registration Module:
  • Enrollment of cameras and data storage.
  • Administration of geotagged data.
2. Module for Geotagging:
  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.
3. Object Detection and failure detection:
  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.
4. Alerting:
  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.
5. Command and Control Center Module:
  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.
Goals to achieve
  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques
Achievements
  • Qualified for preliminary round of IEEE YESIST12.
  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)
  • Presented project idea for City institute of disaster Management(BMC)
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
3 stars
Watchers
1 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
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('^' + ".*" + '

Skip to content
BranchesTags
Repository files navigation
Project Name: GeoGuard
Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.
Video Demonstration:
GeoGuard.2024.mp4
Techstack:
  • Frontend:
    • Powered by React
    • Integrated with Google Maps API
  • Database:
    • Managed using Firebase
  • Backend:
    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics
  • Hosting:
    • Hosted on Google App Engine
    • Load balancer included for optimal performance
How to Setup Locally
Setup ML Model
💻 Install
#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt
📸 Execute
python3 -m main
Setup Dashboard
💻 Install
# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install
📸 Execute
#Run servercd server
npm start
#on a separate cmd Run client
npm start
Modules
1. Camera Registration Module:
  • Enrollment of cameras and data storage.
  • Administration of geotagged data.
2. Module for Geotagging:
  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.
3. Object Detection and failure detection:
  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.
4. Alerting:
  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.
5. Command and Control Center Module:
  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.
Goals to achieve
  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques
Achievements
  • Qualified for preliminary round of IEEE YESIST12.
  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)
  • Presented project idea for City institute of disaster Management(BMC)
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
3 stars
Watchers
1 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
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
Repository files navigation
Project Name: GeoGuard
Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.
Video Demonstration:
GeoGuard.2024.mp4
Techstack:
  • Frontend:
    • Powered by React
    • Integrated with Google Maps API
  • Database:
    • Managed using Firebase
  • Backend:
    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics
  • Hosting:
    • Hosted on Google App Engine
    • Load balancer included for optimal performance
How to Setup Locally
Setup ML Model
💻 Install
#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt
📸 Execute
python3 -m main
Setup Dashboard
💻 Install
# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install
📸 Execute
#Run servercd server
npm start
#on a separate cmd Run client
npm start
Modules
1. Camera Registration Module:
  • Enrollment of cameras and data storage.
  • Administration of geotagged data.
2. Module for Geotagging:
  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.
3. Object Detection and failure detection:
  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.
4. Alerting:
  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.
5. Command and Control Center Module:
  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.
Goals to achieve
  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques
Achievements
  • Qualified for preliminary round of IEEE YESIST12.
  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)
  • Presented project idea for City institute of disaster Management(BMC)
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
3 stars
Watchers
1 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
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
Repository files navigation
Project Name: GeoGuard
Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.
Video Demonstration:
GeoGuard.2024.mp4
Techstack:
  • Frontend:
    • Powered by React
    • Integrated with Google Maps API
  • Database:
    • Managed using Firebase
  • Backend:
    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics
  • Hosting:
    • Hosted on Google App Engine
    • Load balancer included for optimal performance
How to Setup Locally
Setup ML Model
💻 Install
#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt
📸 Execute
python3 -m main
Setup Dashboard
💻 Install
# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install
📸 Execute
#Run servercd server
npm start
#on a separate cmd Run client
npm start
Modules
1. Camera Registration Module:
  • Enrollment of cameras and data storage.
  • Administration of geotagged data.
2. Module for Geotagging:
  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.
3. Object Detection and failure detection:
  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.
4. Alerting:
  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.
5. Command and Control Center Module:
  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.
Goals to achieve
  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques
Achievements
  • Qualified for preliminary round of IEEE YESIST12.
  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)
  • Presented project idea for City institute of disaster Management(BMC)
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
3 stars
Watchers
1 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
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
Project Name: GeoGuard
Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.
Video Demonstration:
GeoGuard.2024.mp4
Techstack:
  • Frontend:
    • Powered by React
    • Integrated with Google Maps API
  • Database:
    • Managed using Firebase
  • Backend:
    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics
  • Hosting:
    • Hosted on Google App Engine
    • Load balancer included for optimal performance
How to Setup Locally
Setup ML Model
💻 Install
#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt
📸 Execute
python3 -m main
Setup Dashboard
💻 Install
# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install
📸 Execute
#Run servercd server
npm start
#on a separate cmd Run client
npm start
Modules
1. Camera Registration Module:
  • Enrollment of cameras and data storage.
  • Administration of geotagged data.
2. Module for Geotagging:
  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.
3. Object Detection and failure detection:
  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.
4. Alerting:
  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.
5. Command and Control Center Module:
  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.
Goals to achieve
  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques
Achievements
  • Qualified for preliminary round of IEEE YESIST12.
  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)
  • Presented project idea for City institute of disaster Management(BMC)
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
3 stars
Watchers
1 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
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
Project Name: GeoGuard
Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.
Video Demonstration:
GeoGuard.2024.mp4
Techstack:
  • Frontend:
    • Powered by React
    • Integrated with Google Maps API
  • Database:
    • Managed using Firebase
  • Backend:
    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics
  • Hosting:
    • Hosted on Google App Engine
    • Load balancer included for optimal performance
How to Setup Locally
Setup ML Model
💻 Install
#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt
📸 Execute
python3 -m main
Setup Dashboard
💻 Install
# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install
📸 Execute
#Run servercd server
npm start
#on a separate cmd Run client
npm start
Modules
1. Camera Registration Module:
  • Enrollment of cameras and data storage.
  • Administration of geotagged data.
2. Module for Geotagging:
  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.
3. Object Detection and failure detection:
  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.
4. Alerting:
  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.
5. Command and Control Center Module:
  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.
Goals to achieve
  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques
Achievements
  • Qualified for preliminary round of IEEE YESIST12.
  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)
  • Presented project idea for City institute of disaster Management(BMC)
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
3 stars
Watchers
1 watching
Forks
4 forks
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, '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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Project Name: GeoGuard
Private cameras in businesses, homes, and institutions play a crucial role in enhancing public safety and crime detection. Many private cameras lack clear locations, making it difficult for the police to efficiently access relevant video footage during investigations in specific crime-prone areas.
Video Demonstration:
GeoGuard.2024.mp4
Techstack:
  • Frontend:
    • Powered by React
    • Integrated with Google Maps API
  • Database:
    • Managed using Firebase
  • Backend:
    • Python communicates with ML model
    • ML model consists of YOLOv8 and Vertex AI along with ultralytics
  • Hosting:
    • Hosted on Google App Engine
    • Load balancer included for optimal performance
How to Setup Locally
Setup ML Model
💻 Install
#direct to ml foldercd yolov8-live-master
# create python virtual environment
python3 -m venv venv
# activate the virtual environmentsource venv/bin/activate
# install dependencies
pip install -r requirements.txt
📸 Execute
python3 -m main
Setup Dashboard
💻 Install
# install node_modules for client
npm install
#direct to Servercd server
# install node_modules for server
npm install
📸 Execute
#Run servercd server
npm start
#on a separate cmd Run client
npm start
Modules
1. Camera Registration Module:
  • Enrollment of cameras and data storage.
  • Administration of geotagged data.
2. Module for Geotagging:
  • Using the Google Maps API to geotag the approved camera area and introduction.
  • Interactive map will help the Control center module to strategically plan the layout to avoid any casualties.
3. Object Detection and failure detection:
  • Analysis of video streams from registered cameras.
  • Identification of specific objects using deep learning and object detection.
  • Detection of camera failures.
4. Alerting:
  • Real-time communication and alert generation based on detected objects.
  • Notification of camera failures to the Owner and Control Center.
5. Command and Control Center Module:
  • Confirmation of camera registration and alert subscription.
  • Map-based interface for displaying alerts and camera locations.
  • Interface for contacting camera owners, requesting access to video footage, and dispatching police units.
  • Reception and processing of alerts from the Object Detection and Failure Detection Module.
Goals to achieve
  • Planning on switching to SQL based database for better scalability
  • Achieving camera feed from local IP to public IP
  • Implementing cloud-based storage to store CCTV footage using different encryption and compression techniques
Achievements
  • Qualified for preliminary round of IEEE YESIST12.
  • Currently developing under guidance of Rajasthan Police (Finalist at Rajasthan Police Hackathon 1.0)
  • Presented project idea for City institute of disaster Management(BMC)
About
No description, website, or topics provided.
Resources
Readme
Activity
Stars
3 stars
Watchers
1 watching
Forks
4 forks
Report repository
Releases
Packages
Used by
Contributors
Languages