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Number recognizer

It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)

It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.

Installation

Please install it in this order, because openCV can be crashed. For GPU:

For CPU and GPU:

  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html After installation add TesseractOCR folder to PATH (in windows)

  • Install pythorch: https://pytorch.org/get-started/locally/

  • Install openCV for python: https://opencv.org/get-started/

  • Install easyOCR: https://github.com/JaidedAI/EasyOCR

    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:

    pip uninstall opencv-python-headless I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install

  • Install python packadges for visualisation and animation:

    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process) Example requirements file in repository (for gpu and cpu)

Features:

  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use

Plans:

  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image

About

Easy package for numeric recognizing on videos

Topics

computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython

Resources

Readme
Activity

Stars

0 stars

Watchers

1 watching

Forks

0 forks
Report repository

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Contributors

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, 'i'); if (__m === '*' || __re.test(location.href)) { injectUserscript("// Add copy buttons to all 
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}
} 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
Number recognizer
It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)
It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.
Installation
Please install it in this order, because openCV can be crashed.
For GPU:
For CPU and GPU:
  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html
After installation add TesseractOCR folder to PATH (in windows)
  • Install pythorch: https://pytorch.org/get-started/locally/
  • Install openCV for python: https://opencv.org/get-started/
  • Install easyOCR: https://github.com/JaidedAI/EasyOCR
    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:
    pip uninstall opencv-python-headless
I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install
  • Install python packadges for visualisation and animation:
    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process)
Example requirements file in repository (for gpu and cpu)
Features:
  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use
Plans:
  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image
About
Easy package for numeric recognizing on videos
Topics
computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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
Number recognizer
It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)
It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.
Installation
Please install it in this order, because openCV can be crashed.
For GPU:
For CPU and GPU:
  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html
After installation add TesseractOCR folder to PATH (in windows)
  • Install pythorch: https://pytorch.org/get-started/locally/
  • Install openCV for python: https://opencv.org/get-started/
  • Install easyOCR: https://github.com/JaidedAI/EasyOCR
    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:
    pip uninstall opencv-python-headless
I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install
  • Install python packadges for visualisation and animation:
    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process)
Example requirements file in repository (for gpu and cpu)
Features:
  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use
Plans:
  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image
About
Easy package for numeric recognizing on videos
Topics
computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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
Number recognizer
It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)
It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.
Installation
Please install it in this order, because openCV can be crashed.
For GPU:
For CPU and GPU:
  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html
After installation add TesseractOCR folder to PATH (in windows)
  • Install pythorch: https://pytorch.org/get-started/locally/
  • Install openCV for python: https://opencv.org/get-started/
  • Install easyOCR: https://github.com/JaidedAI/EasyOCR
    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:
    pip uninstall opencv-python-headless
I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install
  • Install python packadges for visualisation and animation:
    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process)
Example requirements file in repository (for gpu and cpu)
Features:
  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use
Plans:
  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image
About
Easy package for numeric recognizing on videos
Topics
computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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
Number recognizer
It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)
It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.
Installation
Please install it in this order, because openCV can be crashed.
For GPU:
For CPU and GPU:
  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html
After installation add TesseractOCR folder to PATH (in windows)
  • Install pythorch: https://pytorch.org/get-started/locally/
  • Install openCV for python: https://opencv.org/get-started/
  • Install easyOCR: https://github.com/JaidedAI/EasyOCR
    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:
    pip uninstall opencv-python-headless
I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install
  • Install python packadges for visualisation and animation:
    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process)
Example requirements file in repository (for gpu and cpu)
Features:
  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use
Plans:
  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image
About
Easy package for numeric recognizing on videos
Topics
computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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
Number recognizer
It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)
It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.
Installation
Please install it in this order, because openCV can be crashed.
For GPU:
For CPU and GPU:
  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html
After installation add TesseractOCR folder to PATH (in windows)
  • Install pythorch: https://pytorch.org/get-started/locally/
  • Install openCV for python: https://opencv.org/get-started/
  • Install easyOCR: https://github.com/JaidedAI/EasyOCR
    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:
    pip uninstall opencv-python-headless
I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install
  • Install python packadges for visualisation and animation:
    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process)
Example requirements file in repository (for gpu and cpu)
Features:
  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use
Plans:
  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image
About
Easy package for numeric recognizing on videos
Topics
computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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
Number recognizer
It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)
It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.
Installation
Please install it in this order, because openCV can be crashed.
For GPU:
For CPU and GPU:
  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html
After installation add TesseractOCR folder to PATH (in windows)
  • Install pythorch: https://pytorch.org/get-started/locally/
  • Install openCV for python: https://opencv.org/get-started/
  • Install easyOCR: https://github.com/JaidedAI/EasyOCR
    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:
    pip uninstall opencv-python-headless
I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install
  • Install python packadges for visualisation and animation:
    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process)
Example requirements file in repository (for gpu and cpu)
Features:
  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use
Plans:
  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image
About
Easy package for numeric recognizing on videos
Topics
computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython
Resources
Readme
Activity
Stars
0 stars
Watchers
1 watching
Forks
0 forks
Report repository
Releases
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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Number recognizer
It is number recognizer on videos. You can configurate video preprocessing, vision window size and check results after recognizing on flow. This project in active working and I use it to get lab research results without having to look at the indicators every minute)
It uses easyOCR package to recognize. For details and installation instructions see: https://github.com/JaidedAI/EasyOCR. Image processing packadge is OpenCV.
Installation
Please install it in this order, because openCV can be crashed.
For GPU:
For CPU and GPU:
  • Install Tesseract OCR engine (necessary for easyOCR package) : https://tesseract-ocr.github.io/tessdoc/Installation.html
After installation add TesseractOCR folder to PATH (in windows)
  • Install pythorch: https://pytorch.org/get-started/locally/
  • Install openCV for python: https://opencv.org/get-started/
  • Install easyOCR: https://github.com/JaidedAI/EasyOCR
    After installation easyOCR restart your computer and after delete opencv-python-headless package to fix crashing with MethodNotImplemented error from cv2.selectROI function (it provides image cutting interactively), because opencv-python-headless not implement GUI functions and used for servers:
    pip uninstall opencv-python-headless
I can't fix it yet, and can't understand this problem, but several combinations this actions may help to install
  • Install python packadges for visualisation and animation:
    • matplotlib
    • PyQt5(for animation in separate window)
    • pympl (for animation in jupyter notebook)
    • tqdm (for animate recognize process)
Example requirements file in repository (for gpu and cpu)
Features:
  • Process every video frame to increase recognizing quality interactively
  • Choose framerate you need to recognize
  • Cut several areas to recognize numbers on playing video
  • Configure custom pattern using regexp to check the correctness of recognizing and use slightly wrong results to combine them to get fully correct with verbose
  • Configure smart searching of image preprocessing configurations in case uncorrect recognizing
  • Easy to configure and use
Plans:
  • Add contrast and more options to image processor
  • Update image processor sweep to find best conditions faster
  • Add value corrector which uses adjacent frames
  • Add timer and zoom on video
  • Contain it to docker image
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Easy package for numeric recognizing on videos
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computer-visioneasy-to-useeasyocrocr-pythonocr-recognitionopencvpython
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