Repository files navigation

EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start
, '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

Repository files navigation

EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start
, '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

Repository files navigation

EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start
, '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

Repository files navigation

EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start
, '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

Repository files navigation

EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start
, '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

Repository files navigation

EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start
, '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

Repository files navigation

EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start
, '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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EasyWay

View Project Description as PDF | Download Project Description as Word Document

File Structure

Our application is structured as follows:

File NameDescription
ProjectDocsThis folder contains all the Project Deliverable files featured on the project Wiki page.
TeamPhotosThis folder contains the photos of each team member that are used on the project Wiki page.
clientThis folder contains the codes for Front End.
dbThis folder contains the database schema and dummy data.
serverThis folder contains the codes for Back End server.

Technology Stack:

  • Framework : Angular
  • Backend : GoLang, Flask
  • Database : MySQL (GORM Library)
  • Version Control: Git
  • Code Editor : Visual Studio Code

Project Board:

Link : https://github.com/users/ksharma67/projects/2

API Documentation:

Link : https://documenter.getpostman.com/view/23815648/2s93eSZant

Running Backend Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Make sure you have mysql installed and correctly set up.
  • Create a new database in MySQL using:
mysql -u root -p

Enter mysql password, then run:

create database easyWay;
  • Goto config.go and update your mysql password
cd server/config/
code config.go
  • Now navigate to server folder and run go server:
cd ./server/
go run main.go

Ignore any errors as it will check for required datatables (show the error), then automatically creates the datatables.

Running Backend Server - Object Detection Server:

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
cd ./server/
  • Install the required libraries
# TensorFlow CPU
pip install -r requirements.txt
# TensorFlow GPU
pip install -r requirements-gpu.txt
  • For Linux: Let's download official yolov3 weights pretrained on COCO dataset.
# Downloading yolov3 weights
wget https://pjreddie.com/media/files/yolov3.weights -O weights/yolov3.weights
  • Load the weights using load_weights.py script. This will convert the yolov3 weights into TensorFlow .ckpt model files!
# Loading yolov3 weights
python load_weights.py
  • Starting the Flask Server
python app.py

Running Frontend Server:

Link : https://easywayapp.netlify.app

  • Clone the repository
git clone https://github.com/htmw/EasyWay.git
  • Install NodeJS LTS version from https://nodejs.org/en/ for your Operating System.
  • Navigate to client folder and install required libraries:
cd ./client/
npm install
  • In case of any error run audit and install once more:
npm audit fix --force && npm install
  • Run the Angular Server:
npm start