├── .gitignore ├── LICENSE ├── README.md ├── assets ├── airplane-plot.png ├── airplane.png ├── boat.png ├── bug-on-cam.png ├── bus.png ├── camera.png ├── car.png ├── ccs-styled-plots.png ├── chicago-bus.png ├── chicago-buses.png ├── cosmo-cam.png ├── environments.png ├── favicon.png ├── google-maps.png ├── heroku-error.png ├── map-plots.png ├── map-with-cameras.png ├── supervision-tn.png ├── train.png └── vdot.png ├── mk14.py ├── requirements.txt ├── static ├── assets │ ├── airplane-plot.png │ ├── airplane.png │ ├── boat.png │ ├── bug-on-cam.png │ ├── bus.png │ ├── camera.png │ ├── car.png │ ├── ccs-styled-plots.png │ ├── chicago-bus.png │ ├── chicago-buses.png │ ├── cosmo-cam.png │ ├── environments.png │ ├── favicon.png │ ├── google-maps.png │ ├── heroku-error.png │ ├── map-plots.png │ ├── map-with-cameras.png │ ├── supervision-tn.png │ ├── train.png │ └── vdot.png ├── cameras │ ├── alberta.json │ ├── london.geojson │ ├── maryland.json │ ├── nothern-ireland.geojson │ ├── toronto.json │ └── virginia.geojson ├── css │ ├── all.css │ └── leaflet.awesome-markers.css └── js │ ├── leaflet.awesome-markers.js │ └── supervision.js └── templates └── index.html /.gitignore: -------------------------------------------------------------------------------- 1 | .env 2 | resources 3 | -------------------------------------------------------------------------------- /LICENSE: -------------------------------------------------------------------------------- 1 | 2 | MIT License 3 | 4 | Copyright (c) 2022 Blue Cosmo 5 | 6 | Permission is hereby granted, free of charge, to any person obtaining a copy 7 | of this software and associated documentation files (the "Software"), to deal 8 | in the Software without restriction, including without limitation the rights 9 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 10 | copies of the Software, and to permit persons to whom the Software is 11 | furnished to do so, subject to the following conditions: 12 | 13 | The above copyright notice and this permission notice shall be included in all 14 | copies or substantial portions of the Software. 15 | 16 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 17 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 18 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 19 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 20 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 21 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 22 | SOFTWARE. -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | [ccs]: https://cosmodiumcs.com 5 | [youtube]: https://www.youtube.com/c/CosmodiumCS 6 | [supervision]: https://marks.cosmodiumcs.com/marks/mk14-supervision/ 7 | 8 | 9 | # SuperVision 10 | > Blue Cosmo | 07/02/22 11 | 12 | --- 13 | 14 | 15 | ``` 16 | .::::::. ... :::::::::::::. .,:::::: :::::::.. 17 | ;;;` ` ;; ;;; `;;;```.;;;;;;;'''' ;;;;``;;;; 18 | '[==/[[[[,[[' [[[ `]]nnn]]' [[cccc [[[,/[[[' 19 | ''' $$$ $$$ $$$"" $$"""" $$$$$$c 20 | 88b dP88 .d888 888o 888oo,__ 888b "88bo, 21 | "YMmMY" "YmmMMMM"" YMMMb """"YUMMMMMMM "W" 22 | :~?J555J?~: 23 | ::: .::.::: .::::::. ::: .~YG&@B5J?J5B@&GY~. :::. :::. 24 | ';;, ,;;;' ;;;;;;` ` ;;; :JB@@@B~.~?J7~.~B@@@BJ: `;;;;, `;;; 25 | \[[ .[[/ [[['[==/[[[[,[[[ .5&@@@@&: P@@G^PP :&@@@@&5 [[[[[. '[[ 26 | Y$c.$$" $$$ ''' $$$$ .5&@@@@&: P@@@&@P :&@@@@&5. $$$ "Y$c$$ 27 | Y88P 888 88b dP888 :JB@@@B~.~?YJ~.~B@@@BJ: 888 Y88 28 | MP MMM "YMmMY" MMM .~YB&@B5J?J5B@&BY~. MMM YM 29 | :~?J555J?~: 30 | ``` 31 | 32 | 33 | ## Disclaimer: 34 | SuperVision serves to aid security research and become a reminder of the level of government surveillance that exists today. SuperVision got all its shit from a lot of googling, I did this in my spare time, I can only imagine the level of automated surveillance the government is capable of. 35 | 36 | Also note that Supervision is rendering a lot of data, so **it may take a fair bit of time to render the map** [no more than 20-30 secs]. 37 | 38 | 39 | ## Overview: 40 | [SuperVision][supervision] is an open source *"Google Maps"* for hackers developed by [CosmodiumCS][ccs]. SuperVision's map centralizes public data and maps it. Allowing you to see traffic cameras, transportation, and other data systems **in live time**. It is developed with a type of hacking called "Public Data Hacking" [PDH]. This is basically the process in which you exploit data thats publically available. Whats cool about PDH is that its completely legal, because the data we exploit is already publically available. So by the magical powers of Python, JavaScript, and several markup languages, we generate a powerful map that is ready to use whenever you need! 41 | 42 | --- 43 | 44 | 45 | ![SuperVision Map](https://github.com/CosmodiumCS/SuperVision/blob/main/assets/ccs-styled-plots.png?raw=true) 46 | 47 | --- 48 | 49 | 50 | **How It Works:** 51 | 52 | SuperVision works by using Python to generate Keyhole Markup Language [KML] files. KML files are used to map geographic data. There is a [KML](https://github.com/CosmodiumCS/SuperVision/tree/main/kml) directory that contains all of the generated KML files used in this project. **These files CAN be imported into Google Earth** and you will be able to view all of the markers showing the cameras and other public data that SuperVision has mapped. But Google Earth has two problems... 53 | 54 | 1. Google Earth is **NOT** open source 55 | 2. Google Earth only maps data statically 56 | 57 | SuperVision's open source magic allows us to do so much more than what propriatary software limited us to. SuperVision has not only mapped thing like cameras, but it can track live data like the locations of public transportation. We can fully customize the tracking of public data to the fullest extent possible [with a lot of debugging of course XP]. 58 | 59 | --- 60 | 61 | 62 | [![Devlog One](https://github.com/CosmodiumCS/SuperVision/blob/main/assets/supervision-tn.png?raw=true)](https://www.youtube.com/watch?v=knagAWTn7FQ "SuperVision : The Hacker Google Mapper") 63 | 64 | --- 65 | 66 | Watch the first devlog for SuperVision now!! It will give you an update on what the project is and how it was built in the best way possible :D 67 | 68 | 69 | ## Resources: 70 | - [SuperVision][supervision] 71 | - [YouTube Video](https://youtu.be/knagAWTn7FQ) 72 | - [YouTube Channel][youtube] 73 | - [Website][ccs] 74 | 75 | 76 | ## Requirements: 77 | - A Modern Web Browser 78 | - i.e [Chrome, Firefox, Opera, Safari] 79 | - An Internet Connection 80 | 81 | 82 | ## Local Hosting 83 | **SuperVision does have a website [here][supervision]** but if you wish to run it locally you can clone the repository and run the [main.py](https://github.com/CosmodiumCS/SuperVision/blob/main/main.py) file. You then can navigate to `127.0.0.1:5000` in your browser to view the map. 84 | 85 | 86 | ## What Can SuperVision Track? 87 | 88 | ### Cameras 89 | 90 | --- 91 | 92 | 93 | ![Cosmo Camera](https://github.com/CosmodiumCS/SuperVision/blob/main/assets/cosmo-cam.png) 94 | 95 | --- 96 | 97 | SuperVision is capable of plotting traffic, security, and other cameras on its map. The above is a photo of a traffic camera showing developer [Blue Cosmo][ccs] at an intersection. This shows the vast amount of possible surveillance with a tool as simple as this. 98 | 99 | ### Vehicles 100 | 101 | --- 102 | 103 | 104 | ![Chicago Buses](https://github.com/CosmodiumCS/SuperVision/blob/main/assets/chicago-bus.png?raw=true) 105 | 106 | --- 107 | 108 | SuperVision is capable of plotting live data. Above we can see the current positions of buses in chicago. Every 10 seconds SuperVision will update any data that it has plotted live for a more consistent flow of where certain live data is on the map. 109 | 110 | ### Aircraft 111 | 112 | --- 113 | 114 | 115 | ![Airplanes](https://github.com/CosmodiumCS/SuperVision/blob/main/assets/airplane-plot.png?raw=true) 116 | 117 | --- 118 | 119 | SuperVision plots the positions of aircraft in live time. Every 10 seconds, SuperVision updates their positions and displays their country of origin in a popup [when hovered]. 120 | 121 | 122 | ## Data Policy 123 | - SuperVision **only** asks for your device's approximate location. If you say yes it will display the available data closest to you. If you say no, it will display all the full map. 124 | - SuperVision **does not** collect any user data...read the code 125 | 126 | 127 | ## Credits 128 | The original concept comes from an old friend of mine, Shepherd. He had the idea to map specific camera locations to kml files and map them on Google Earth. I joined the project and discovered methods of automatically mapping data instead of doing such a thing manually. But after a falling out I took the project to the next step by creating a dynamic mapping environment outside of Google Earth. This has allowed me to map not only all the cameras simultaneously, but also to map live data in real time. 129 | 130 | --- 131 | 132 | 133 | © 2022 by Cosmodium CyberSecurity, LLC 134 | -------------------------------------------------------------------------------- /assets/airplane-plot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CosmodiumCS/MK14-SuperVision/b1b48a99956d48c3d4639b60c43041ab25bb3ccf/assets/airplane-plot.png -------------------------------------------------------------------------------- /assets/airplane.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CosmodiumCS/MK14-SuperVision/b1b48a99956d48c3d4639b60c43041ab25bb3ccf/assets/airplane.png -------------------------------------------------------------------------------- /assets/boat.png: -------------------------------------------------------------------------------- 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import os 7 | import random 8 | import requests 9 | import xmltodict 10 | from dotenv import load_dotenv 11 | from flask import Flask, render_template, jsonify 12 | 13 | # environment variables 14 | load_dotenv() 15 | CTA_KEY = os.getenv('CTA_KEY') 16 | 17 | app = Flask(__name__, static_folder='static', static_url_path='/mk14/static') 18 | app.config['APPLICATION_ROOT'] = '/mk14' 19 | 20 | def list_files(directory): 21 | files = [] 22 | for filename in os.listdir(directory): 23 | path = os.path.join(directory, filename) 24 | if os.path.isfile(path): 25 | files.append(filename) 26 | return files 27 | 28 | # main page 29 | @app.route('/mk14/') 30 | def mk14(): 31 | camera_list = list_files('/var/www/html/mk14-supervision/static/cameras') 32 | return render_template('index.html', camera_locations=camera_list) 33 | 34 | @app.route('/mk14/api/transit') 35 | def transit(): 36 | 37 | # randomly generated cameras for testing / debugging 38 | cameras = [ 39 | {'lat': 51.5074 + random.uniform(-0.1, 0.1), 'lon': -0.1278 + random.uniform(-0.1, 0.1), 'popup': 'Camera 1'}, 40 | {'lat': 51.5074 + random.uniform(-0.1, 0.1), 'lon': -0.1278 + random.uniform(-0.1, 0.1), 'popup': 'Camera 2'}, 41 | ] 42 | return jsonify(cameras) 43 | 44 | # cta_routes_url = f'http://www.ctabustracker.com/bustime/api/v2/getroutes?key={CTA_KEY}' 45 | # cta_bus_url = f'http://ctabustracker.com/bustime/api/v2/getvehicles?key={CTA_KEY}&rt=' 46 | # vehicles_info = [] 47 | 48 | # try: 49 | # response = requests.get(cta_routes_url) 50 | # response.raise_for_status() # Raise an exception for bad responses 51 | 52 | # xml_dict = xmltodict.parse(response.content) 53 | # rt_numbers = [str(route['rt']) for route in xml_dict.get('bustime-response', {}).get('route', [])] 54 | 55 | # for route in rt_numbers: 56 | # bus_url = cta_bus_url + str(route) 57 | # cta_bus = requests.get(bus_url) 58 | # cta_bus_json = xmltodict.parse(cta_bus.content) 59 | 60 | # # works up to here :) 61 | # vehicles = cta_bus_json.get('bustime-response', {}).get('vehicle', []) 62 | # if isinstance(vehicles, dict): 63 | # vehicles = [vehicles] 64 | 65 | # for vehicle in vehicles: 66 | # vid = int(vehicle.get('vid')) 67 | # lat = float(vehicle.get('lat')) 68 | # lon = float(vehicle.get('lon')) 69 | # vehicles_info.append({'vid': vid, 'lat': lat, 'lon': lon}) 70 | 71 | # return jsonify(vehicles_info) 72 | 73 | # except requests.exceptions.RequestException as e: 74 | # # Handle request exceptions (e.g., connection error, timeout) 75 | # return jsonify({'error': str(e)}), 500 # Return an error response with HTTP status code 500 76 | 77 | # except xmltodict.expat.ExpatError as e: 78 | # # Handle XML parsing errors 79 | # return jsonify({'error': 'Error parsing XML: ' + str(e)}), 500 # Return an error response with HTTP status code 500 80 | 81 | # main code, run app 82 | if __name__ == '__main__': 83 | # app.run(debug=True) 84 | app.run(host='0.0.0.0', port=5000) 85 | -------------------------------------------------------------------------------- /requirements.txt: -------------------------------------------------------------------------------- 1 | blinker==1.7.0 2 | certifi==2023.11.17 3 | charset-normalizer==3.3.2 4 | click==8.1.7 5 | Flask==3.0.0 6 | idna==3.6 7 | itsdangerous==2.1.2 8 | Jinja2==3.1.2 9 | MarkupSafe==2.1.3 10 | python-dotenv==1.0.0 11 | requests==2.31.0 12 | urllib3==2.1.0 13 | Werkzeug==3.0.1 14 | xmltodict==0.13.0 15 | -------------------------------------------------------------------------------- /static/assets/airplane-plot.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/CosmodiumCS/MK14-SuperVision/b1b48a99956d48c3d4639b60c43041ab25bb3ccf/static/assets/airplane-plot.png -------------------------------------------------------------------------------- /static/assets/airplane.png: 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https://trafficwatchni.com/twni/cameras/static?id=58" 30 | }, 31 | "geometry": { 32 | "type": "Point", 33 | "coordinates": [ 34 | 0, 35 | 0 36 | ] 37 | } 38 | }, 39 | { 40 | "type": "Feature", 41 | "properties": { 42 | "description": "M22 - Dunsilly Roundabout", 43 | "url": " https://trafficwatchni.com/twni/cameras/static?id=210" 44 | }, 45 | "geometry": { 46 | "type": "Point", 47 | "coordinates": [ 48 | 0, 49 | 0 50 | ] 51 | } 52 | }, 53 | { 54 | "type": "Feature", 55 | "properties": { 56 | "description": "Lodge Rd Rand#39;bout Newbridge Coleraine", 57 | "url": " https://trafficwatchni.com/twni/cameras/static?id=60" 58 | }, 59 | "geometry": { 60 | "type": "Point", 61 | "coordinates": [ 62 | 0, 63 | 0 64 | ] 65 | } 66 | }, 67 | { 68 | "type": "Feature", 69 | "properties": { 70 | "description": "Lodge Rd Rand#39;bout Lodge Coleraine", 71 | "url": " https://trafficwatchni.com/twni/cameras/static?id=62" 72 | }, 73 | "geometry": { 74 | "type": "Point", 75 | "coordinates": [ 76 | 0, 77 | 0 78 | ] 79 | } 80 | }, 81 | { 82 | "type": "Feature", 83 | "properties": { 84 | "description": "Kilowen St Coleraine", 85 | "url": " https://trafficwatchni.com/twni/cameras/static?id=67" 86 | }, 87 | "geometry": { 88 | "type": "Point", 89 | "coordinates": [ 90 | 0, 91 | 0 92 | ] 93 | } 94 | }, 95 | { 96 | "type": "Feature", 97 | "properties": { 98 | "description": "A2 Shore Rd - Trooperslane", 99 | "url": " Carrick" 100 | }, 101 | "geometry": { 102 | "type": "Point", 103 | "coordinates": [ 104 | 0, 105 | 0 106 | ] 107 | } 108 | }, 109 | { 110 | "type": "Feature", 111 | "properties": { 112 | "description": "Westlink - York Street", 113 | "url": " https://trafficwatchni.com/twni/cameras/static?id=55" 114 | }, 115 | "geometry": { 116 | "type": "Point", 117 | "coordinates": [ 118 | 0, 119 | 0 120 | ] 121 | } 122 | }, 123 | { 124 | "type": "Feature", 125 | "properties": { 126 | "description": "Westlink - Hospital", 127 | "url": " https://trafficwatchni.com/twni/cameras/static?id=214" 128 | 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2758 | "description": "Craigavon Bridge", 2759 | "url": "https://trafficwatchni.com/twni/cameras/static?id=72" 2760 | }, 2761 | "geometry": { 2762 | "type": "Point", 2763 | "coordinates": [ 2764 | -7.3164636, 2765 | 54.989784 2766 | ] 2767 | } 2768 | }, 2769 | { 2770 | "type": "Feature", 2771 | "properties": { 2772 | "description": "Buncrana Road", 2773 | "url": "https://trafficwatchni.com/twni/cameras/static?id=70" 2774 | }, 2775 | "geometry": { 2776 | "type": "Point", 2777 | "coordinates": [ 2778 | -7.3579137, 2779 | 55.0335509 2780 | ] 2781 | } 2782 | }, 2783 | { 2784 | "type": "Feature", 2785 | "properties": { 2786 | "description": "Foyle Bridge", 2787 | "url": "https://trafficwatchni.com/twni/cameras/static?id=20" 2788 | }, 2789 | "geometry": { 2790 | "type": "Point", 2791 | "coordinates": [ 2792 | -7.4442503, 2793 | 52.7391422 2794 | ] 2795 | } 2796 | } 2797 | ] 2798 | } 2799 | -------------------------------------------------------------------------------- /static/css/leaflet.awesome-markers.css: -------------------------------------------------------------------------------- 1 | /* 2 | Author: L. Voogdt 3 | License: MIT 4 | Version: 1.0 5 | */ 6 | 7 | /* Marker setup */ 8 | .awesome-marker { 9 | background: url('images/markers-soft.png') no-repeat 0 0; 10 | width: 35px; 11 | height: 46px; 12 | position:absolute; 13 | left:0; 14 | top:0; 15 | display: block; 16 | text-align: center; 17 | } 18 | 19 | .awesome-marker-shadow { 20 | background: url('images/markers-shadow.png') no-repeat 0 0; 21 | width: 36px; 22 | height: 16px; 23 | } 24 | 25 | /* Retina displays */ 26 | @media (min--moz-device-pixel-ratio: 1.5),(-o-min-device-pixel-ratio: 3/2), 27 | (-webkit-min-device-pixel-ratio: 1.5),(min-device-pixel-ratio: 1.5),(min-resolution: 1.5dppx) { 28 | .awesome-marker { 29 | background-image: url('images/markers-soft@2x.png'); 30 | background-size: 720px 46px; 31 | } 32 | .awesome-marker-shadow { 33 | background-image: url('images/markers-shadow@2x.png'); 34 | background-size: 35px 16px; 35 | } 36 | } 37 | 38 | .awesome-marker i { 39 | color: #333; 40 | margin-top: 10px; 41 | display: inline-block; 42 | font-size: 14px; 43 | } 44 | 45 | .awesome-marker .icon-white { 46 | color: #fff; 47 | } 48 | 49 | /* Colors */ 50 | .awesome-marker-icon-red { 51 | background-position: 0 0; 52 | } 53 | 54 | .awesome-marker-icon-darkred { 55 | background-position: -180px 0; 56 | } 57 | 58 | .awesome-marker-icon-lightred { 59 | background-position: -360px 0; 60 | } 61 | 62 | .awesome-marker-icon-orange { 63 | background-position: -36px 0; 64 | } 65 | 66 | .awesome-marker-icon-beige { 67 | background-position: -396px 0; 68 | } 69 | 70 | .awesome-marker-icon-green { 71 | background-position: -72px 0; 72 | } 73 | 74 | .awesome-marker-icon-darkgreen { 75 | background-position: -252px 0; 76 | } 77 | 78 | .awesome-marker-icon-lightgreen { 79 | background-position: -432px 0; 80 | } 81 | 82 | .awesome-marker-icon-blue { 83 | background-position: -108px 0; 84 | } 85 | 86 | .awesome-marker-icon-darkblue { 87 | background-position: -216px 0; 88 | } 89 | 90 | .awesome-marker-icon-lightblue { 91 | background-position: -468px 0; 92 | } 93 | 94 | .awesome-marker-icon-purple { 95 | background-position: -144px 0; 96 | } 97 | 98 | .awesome-marker-icon-darkpurple { 99 | background-position: -288px 0; 100 | } 101 | 102 | .awesome-marker-icon-pink { 103 | background-position: -504px 0; 104 | } 105 | 106 | .awesome-marker-icon-cadetblue { 107 | background-position: -324px 0; 108 | } 109 | 110 | .awesome-marker-icon-white { 111 | background-position: -574px 0; 112 | } 113 | 114 | .awesome-marker-icon-gray { 115 | background-position: -648px 0; 116 | } 117 | 118 | .awesome-marker-icon-lightgray { 119 | background-position: -612px 0; 120 | } 121 | 122 | .awesome-marker-icon-black { 123 | background-position: -682px 0; 124 | } 125 | -------------------------------------------------------------------------------- /static/js/leaflet.awesome-markers.js: -------------------------------------------------------------------------------- 1 | /* 2 | Leaflet.AwesomeMarkers, a plugin that adds colorful iconic markers for Leaflet, based on the Font Awesome icons 3 | (c) 2012-2013, Lennard Voogdt 4 | 5 | http://leafletjs.com 6 | https://github.com/lvoogdt 7 | */ 8 | 9 | /*global L*/ 10 | 11 | (function (window, document, undefined) { 12 | "use strict"; 13 | /* 14 | * Leaflet.AwesomeMarkers assumes that you have already included the Leaflet library. 15 | */ 16 | 17 | L.AwesomeMarkers = {}; 18 | 19 | L.AwesomeMarkers.version = '2.0.1'; 20 | 21 | L.AwesomeMarkers.Icon = L.Icon.extend({ 22 | options: { 23 | iconSize: [35, 45], 24 | iconAnchor: [17, 42], 25 | popupAnchor: [1, -32], 26 | shadowAnchor: [10, 12], 27 | shadowSize: [36, 16], 28 | className: 'awesome-marker', 29 | prefix: 'glyphicon', 30 | spinClass: 'fa-spin', 31 | extraClasses: '', 32 | icon: 'home', 33 | markerColor: 'blue', 34 | iconColor: 'white' 35 | }, 36 | 37 | initialize: function (options) { 38 | options = L.Util.setOptions(this, options); 39 | }, 40 | 41 | createIcon: function () { 42 | var div = document.createElement('div'), 43 | options = this.options; 44 | 45 | if (options.icon) { 46 | div.innerHTML = this._createInner(); 47 | } 48 | 49 | if (options.bgPos) { 50 | div.style.backgroundPosition = 51 | (-options.bgPos.x) + 'px ' + (-options.bgPos.y) + 'px'; 52 | } 53 | 54 | this._setIconStyles(div, 'icon-' + options.markerColor); 55 | return div; 56 | }, 57 | 58 | _createInner: function() { 59 | var iconClass, iconSpinClass = "", iconColorClass = "", iconColorStyle = "", options = this.options; 60 | 61 | if(options.icon.slice(0,options.prefix.length+1) === options.prefix + "-") { 62 | iconClass = options.icon; 63 | } else { 64 | iconClass = options.prefix + "-" + options.icon; 65 | } 66 | 67 | if(options.spin && typeof options.spinClass === "string") { 68 | iconSpinClass = options.spinClass; 69 | } 70 | 71 | if(options.iconColor) { 72 | if(options.iconColor === 'white' || options.iconColor === 'black') { 73 | iconColorClass = "icon-" + options.iconColor; 74 | } else { 75 | iconColorStyle = "style='color: " + options.iconColor + "' "; 76 | } 77 | } 78 | 79 | return ""; 80 | }, 81 | 82 | _setIconStyles: function (img, name) { 83 | var options = this.options, 84 | size = L.point(options[name === 'shadow' ? 'shadowSize' : 'iconSize']), 85 | anchor; 86 | 87 | if (name === 'shadow') { 88 | anchor = L.point(options.shadowAnchor || options.iconAnchor); 89 | } else { 90 | anchor = L.point(options.iconAnchor); 91 | } 92 | 93 | if (!anchor && size) { 94 | anchor = size.divideBy(2, true); 95 | } 96 | 97 | img.className = 'awesome-marker-' + name + ' ' + options.className; 98 | 99 | if (anchor) { 100 | img.style.marginLeft = (-anchor.x) + 'px'; 101 | img.style.marginTop = (-anchor.y) + 'px'; 102 | } 103 | 104 | if (size) { 105 | img.style.width = size.x + 'px'; 106 | img.style.height = size.y + 'px'; 107 | } 108 | }, 109 | 110 | createShadow: function () { 111 | var div = document.createElement('div'); 112 | 113 | this._setIconStyles(div, 'shadow'); 114 | return div; 115 | } 116 | }); 117 | 118 | L.AwesomeMarkers.icon = function (options) { 119 | return new L.AwesomeMarkers.Icon(options); 120 | }; 121 | 122 | }(this, document)); 123 | 124 | 125 | 126 | -------------------------------------------------------------------------------- /static/js/supervision.js: -------------------------------------------------------------------------------- 1 | // map 2 | var map = L.map( 3 | "map", 4 | { 5 | center: [0, 0], 6 | crs: L.CRS.EPSG3857, 7 | zoom: 1, 8 | zoomControl: true, 9 | preferCanvas: false 10 | } 11 | ); 12 | L.control.scale().addTo(map); 13 | 14 | // tile layers 15 | var cosmodiumcsTileLayer = L.tileLayer( // cosmodiumcs custom tile layer 16 | "https://api.mapbox.com/styles/v1/cosmodiumcs/cl5cuv2ar000315o5qr197too/tiles/{z}/{x}/{y}?access_token=pk.eyJ1IjoiY29zbW9kaXVtY3MiLCJhIjoiY2w1Y3VucHRjMDZtdjNkb3libjNlMjEyZSJ9.z2TV_0S6PuuIHS847jCq1A", 17 | {attribution: "© CosmodiumCS"} 18 | 19 | ).addTo(map); 20 | var satelliteTileLayer = L.tileLayer('http://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}'); // sattelite tile layer 21 | 22 | // minimap 23 | const miniMap = new L.Control.MiniMap(L.tileLayer('https://{s}.tile.openstreetmap.org/{z}/{x}/{y}.png', { 24 | attribution: 'Map data © OpenStreetMap contributors', 25 | maxZoom: 18 26 | })).addTo(map); 27 | 28 | // geocoder 29 | var geocoder = L.Control.geocoder({ 30 | defaultMarkGeocode: false 31 | }).on('markgeocode', function(e) { 32 | map.fitBounds(e.geocode.bbox); 33 | }).addTo(map); 34 | 35 | // icons 36 | var cameraIcon = L.icon({ 37 | iconUrl: '{{ url_for("static", filename="assets/camera.png") }}', 38 | iconSize: [40, 40], 39 | }); 40 | var busIcon = L.icon({ 41 | iconUrl: '{{ url_for("static", filename="assets/bus.png") }}', 42 | iconSize: [40, 40], 43 | }); 44 | var boatIcon = L.icon({ 45 | iconUrl: '{{ url_for("static", filename="assets/boat.png") }}', 46 | iconSize: [40, 40], 47 | }); 48 | 49 | // var cameraIcon = L.icon({ // cameras 50 | // iconUrl: 'assets/camera.png', 51 | // iconSize: [40, 40], 52 | // }); 53 | // var busIcon = L.icon({ // buses 54 | // iconUrl: 'assets/bus.png', 55 | // iconSize: [40, 40], 56 | // }); 57 | // var boatIcon = L.icon({ // boats 58 | // iconUrl: 'assets/boat.png', 59 | // iconSize: [40, 40], 60 | // }); 61 | 62 | // cluster icons 63 | function cameraClusterIcon(cluster) { // cameras 64 | return L.divIcon({ 65 | html: '
' + cluster.getChildCount() + '
', 66 | className: 'custom-cluster-icon' 67 | }); 68 | } 69 | 70 | // parse json 71 | function parseJSON(jsonFile) { 72 | fetch(jsonFile) 73 | .then(response => response.json()) 74 | .then(data => { 75 | data.forEach(point => { 76 | const camera = L.marker([point.lat, point.lon], {icon: cameraIcon}) 77 | camera.bindPopup(""+point.description+""); 78 | 79 | cameraClusterGroup.addLayer(camera); 80 | 81 | }); 82 | }) 83 | .catch(error => { 84 | console.error('Error fetching JSON data:', error); 85 | }); 86 | } 87 | 88 | // parse geojson 89 | function parseGEO(geojsonFile) { 90 | fetch(geojsonFile) 91 | .then(response => response.json()) 92 | .then(data => { 93 | 94 | const points = L.geoJSON(data, { 95 | onEachFeature: function(feature, layer) { 96 | let url = feature.properties.url; 97 | if (url.endsWith('m3u8')) { 98 | url = "https://www.hlsplayer.org/play?url=" + url.replace(":","%3A").replace("/","%2F"); 99 | } 100 | layer.bindPopup(`${feature.properties.description}`); 101 | }, 102 | pointToLayer: (feature, latlng) => { 103 | const mpoints = L.marker(latlng, {icon: cameraIcon}); 104 | mpoints.bindPopup(data.description) 105 | return mpoints 106 | } 107 | }) 108 | cameraClusterGroup.addLayer(points); 109 | }) 110 | .catch(error => { 111 | console.error('Error fetching JSON data:', error); 112 | }); 113 | } 114 | 115 | // cluster groups 116 | var cameraClusterGroup = L.markerClusterGroup({ // cameras 117 | iconCreateFunction: cameraClusterIcon 118 | }); 119 | 120 | // layer control 121 | var cameraClusterGroup = L.layerGroup([cameraClusterGroup]); // cameras 122 | var transitLayerGroup = L.layerGroup(); 123 | var baseLayers = { 124 | "CosmodiumCS Tiles": cosmodiumcsTileLayer, 125 | "Sattelite Tiles": satelliteTileLayer 126 | }; 127 | var overlays = { 128 | "Cameras": cameraClusterGroup, 129 | "Transit": transitLayerGroup 130 | }; 131 | 132 | L.control.layers(baseLayers, overlays).addTo(map); // add layer control 133 | 134 | // camera array 135 | // var cameraArray = ['cameras/maryland.json', 'cameras/virginia.geojson', 'cameras/london.geojson', 'cameras/nothern-ireland.geojson', 'cameras/alberta.json', 'cameras/toronto.json']; 136 | 137 | // // parse cameras 138 | // cameraArray.forEach((file) => { 139 | // const extension = file.split(".").pop(); // get the file extension 140 | // if (extension === "json") { 141 | // parseJSON(file); // parse json data 142 | // } else if (extension === "geojson") { 143 | // parseGEO(file); // parse geojson data 144 | // } else { 145 | // console.log(`Unsupported file type: ${extension}`); 146 | // } 147 | // }); 148 | 149 | // add cameras to map 150 | // map.addLayer(cameraClusterGroup); 151 | 152 | // new shit 153 | 154 | // Create separate layer groups for cameras and transit vehicles 155 | // var cameraLayerGroup = L.layerGroup().addTo(map); 156 | var transitLayerGroup = L.layerGroup().addTo(map); 157 | 158 | // Function to update markers on a specific layer group 159 | function updateMarkers(layerGroup, apiEndpoint) { 160 | fetch(apiEndpoint) 161 | .then(response => response.json()) 162 | .then(data => { 163 | // Clear existing markers in the specified layer group 164 | layerGroup.clearLayers(); 165 | 166 | // Add new markers to the specified layer group 167 | data.forEach(marker => { 168 | L.marker([marker.lat, marker.lon]) 169 | .addTo(layerGroup) 170 | .bindPopup(marker.popup); 171 | }); 172 | }) 173 | .catch(error => console.error('Error fetching marker data:', error)); 174 | } 175 | 176 | // Initial markers 177 | // updateMarkers(cameraLayerGroup, '/api/cameras'); 178 | updateMarkers(transitLayerGroup, '/api/transit'); 179 | 180 | // Auto-refresh every 5 seconds 181 | setInterval(function () { 182 | // updateMarkers(cameraLayerGroup, '/api/cameras'); 183 | updateMarkers(transitLayerGroup, '/api/transit'); 184 | }, 5000); 185 | 186 | 187 | 188 | // more shit 189 | 190 | 191 | function loadAndPlotCameraData(file) { 192 | fetch(file) 193 | .then(response => response.json()) 194 | .then(data => { 195 | // Add markers for each camera in the loaded data 196 | data.forEach(marker => { 197 | L.marker([marker.lat, marker.lon]) 198 | .addTo(map) 199 | .bindPopup(marker.popup); 200 | }); 201 | }) 202 | .catch(error => console.error('Error fetching camera data:', error)); 203 | } 204 | 205 | // List of locations to load camera data from 206 | var locations = ['maryland', 'london', 'virginia']; 207 | 208 | // Iterate through each location and load camera data 209 | locations.forEach(location => { 210 | var jsonFile = `static/cameras/${location}.json`; // Adjust the path as needed 211 | var geojsonFile = `static/cameras/${location}.geojson`; // Adjust the path as needed 212 | 213 | // Load and plot data from JSON file 214 | parseJSON(jsonFile); 215 | 216 | // Load and plot data from GeoJSON file 217 | parseGEO(geojsonFile); 218 | }); 219 | 220 | 221 | map.addLayer(cameraClusterGroup); 222 | -------------------------------------------------------------------------------- /templates/index.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | 11 | 12 | MK14-SuperVision 13 | 14 | 15 | 16 | 17 | 18 | 19 | 20 | 21 | 22 | 23 | 24 | 25 | 26 | 27 | 28 | 29 | 30 | 31 | 32 | 33 | 34 | 44 | 45 | 46 | 47 |
48 | 49 | 50 | 187 | 188 | 189 | 190 | --------------------------------------------------------------------------------