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Domain > face.fullsoluciones.cl
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AlienVault OTX
Is this malicious?
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DNS Resolutions
Date
IP Address
2025-03-22
190.107.176.11
(
ClassC
)
Port 80
HTTP/1.1 200 OKConnection: Keep-AliveKeep-Alive: timeout5, max100x-powered-by: PHP/7.4.33content-type: text/html; charsetUTF-8content-length: 6831date: Sat, 22 Mar 2025 13:41:24 GMT !DOCTYPE html>html> head> meta charsetutf-8> meta http-equivX-UA-Compatible contentchrome1> title>Webcam Face Detection Using JavaScript, PHP, and MySQL - Edopedia.com/title> !-- Add these JavaScript files from pico.js library --> script srcpicojs/examples/camvas.js>/script> script srcpicojs/pico.js>/script> script srcpicojs/lploc.js>/script> script> var initialized false; function button_callback() { /* (0) check whether were already running face detection */ if(initialized) return; // if yes, then do not initialize everything again /* (1) initialize the pico.js face detector */ var update_memory pico.instantiate_detection_memory(1); // we will use the detecions of the last 1 frame var facefinder_classify_region function(r, c, s, pixels, ldim) {return -1.0;}; var cascadeurl https://raw.githubusercontent.com/nenadmarkus/pico/c2e81f9d23cc11d1a612fd21e4f9de0921a5d0d9/rnt/cascades/facefinder; fetch(cascadeurl).then(function(response) { response.arrayBuffer().then(function(buffer) { var bytes new Int8Array(buffer); facefinder_classify_region pico.unpack_cascade(bytes); console.log(* facefinder loaded); }) }) /* (2) initialize the lploc.js library with a pupil localizer */ var do_puploc function(r, c, s, nperturbs, pixels, nrows, ncols, ldim) {return -1.0, -1.0;}; //var puplocurl ../puploc.bin; var puplocurl https://f002.backblazeb2.com/file/tehnokv-www/posts/puploc-with-trees/demo/puploc.bin fetch(puplocurl).then(function(response) { response.arrayBuffer().then(function(buffer) { var bytes new Int8Array(buffer); do_puploc lploc.unpack_localizer(bytes); console.log(* puploc loaded); }) }) /* (3) get the drawing context on the canvas and define a function to transform an RGBA image to grayscale */ var ctx document.getElementsByTagName(canvas)0.getContext(2d); function rgba_to_grayscale(rgba, nrows, ncols) { var gray new Uint8Array(nrows*ncols); for(var r0; rnrows; ++r) for(var c0; cncols; ++c) // gray 0.2*red + 0.7*green + 0.1*blue grayr*ncols + c (2*rgbar*4*ncols+4*c+0+7*rgbar*4*ncols+4*c+1+1*rgbar*4*ncols+4*c+2)/10; return gray; } /* (4) this function is called each time a video frame becomes available */ var processfn function(video, dt) { // render the video frame to the canvas element and extract RGBA pixel data ctx.drawImage(video, 0, 0); var rgba ctx.getImageData(0, 0, 640, 480).data; // prepare input to `run_cascade` image { pixels: rgba_to_grayscale(rgba, 480, 640), nrows: 480, ncols: 640, ldim: 640 } params { shiftfactor: 0.1, // move the detection window by 10% of its size minsize: 100, // minimum size of a face maxsize: 1000, // maximum size of a face scalefactor: 1.1 // for multiscale processing: resize the detection window by 10% when moving to the higher scale } // run the cascade over the frame and cluster the obtained detections // dets is an array that contains (r, c, s, q) quadruplets // (representing row, column, scale and detection score) dets pico.run_cascade(image, facefinder_classify_region, params); dets update_memory(dets); dets pico.cluster_detections(dets, 0.2); // set IoU threshold to 0.2 // draw detections for(i0; idets.length; ++i) { // check the detection score // if its above the threshold, draw it // (the constant 50.0 is empirical: other cascades might require a different one) if(detsi3>50.0) { var r, c, s; // ctx.beginPath(); ctx.arc(detsi1, detsi0, detsi2/2, 0, 2*Math.PI, false); ctx.lineWidth 3; ctx.strokeStyle red; ctx.stroke(); // // find the eye pupils for each detected face // starting regions for localization are initialized based on the face bounding box // (parameters are set empirically) // first eye r detsi0 - 0.075*detsi2; c detsi1 - 0.175*detsi2; s 0.35*detsi2; r, c do_puploc(r, c, s, 63, image) if(r>0 && c>0) { ctx.beginPath(); ctx.arc(c, r, 1, 0, 2*Math.PI, false); ctx.lineWidth 3; ctx.strokeStyle red; ctx.stroke(); } // second eye r detsi0 - 0.075*detsi2; c detsi1 + 0.175*detsi2; s 0.35*detsi2; r, c do_puploc(r, c, s, 63, image) if(r>0 && c>0) { ctx.beginPath(); ctx.arc(c, r, 1, 0, 2*Math.PI, false); ctx.lineWidth 3; ctx.strokeStyle red; ctx.stroke(); } // At this point, we already know that the human face is detected in webcam. So, Well simply create an image from canvas that is displaying the webcam result in real-time. var can document.getElementsByTagName(canvas)0 var img new Image(); img.src can.toDataURL(image/jpeg, 1.0); // Now, we will send the image to server and process it using PHP. Also, we have to save its path in MySQL database for later use. var data JSON.stringify({ image: img.src }); fetch(save.php, { method: POST, body: data }) .then(function(res){ return res.json(); }) .then(function(data){ return alert( data.message ); }) // This alert statement is a little hack to temporarily stop the execution of script. alert(Face found!); } } } /* (5) instantiate camera handling (see https://github.com/cbrandolino/camvas) */ var mycamvas new camvas(ctx, processfn); /* (6) it seems that everything went well */ initialized true; } /script> /head> body> div> h3>Webcam Face Detection Using JavaScript, PHP, and MySQL by Edopedia.com/h3> p>Click the Start Webcam button below and allow the page to access your webcam./p> p>View Tutorial: a hrefhttps://www.edopedia.com/blog/webcam-face-detection-javascript-php-mysql/ target_blank>https://www.edopedia.com/blog/webcam-face-detection-javascript-php-mysql//a>/p> /div> hr /> p> center> input typebutton valueStart Webcam onclickbutton_callback()> a hrefview.php target_blank>View Saved Images/a> /center> /p> hr /> p> center> canvas width640 height480>/canvas> /center> /p> /body>/html>
Port 443
HTTP/1.1 200 OKConnection: Keep-AliveKeep-Alive: timeout5, max100x-powered-by: PHP/7.4.33content-type: text/html; charsetUTF-8content-length: 6831date: Sat, 22 Mar 2025 13:41:25 GMT !DOCTYPE html>html> head> meta charsetutf-8> meta http-equivX-UA-Compatible contentchrome1> title>Webcam Face Detection Using JavaScript, PHP, and MySQL - Edopedia.com/title> !-- Add these JavaScript files from pico.js library --> script srcpicojs/examples/camvas.js>/script> script srcpicojs/pico.js>/script> script srcpicojs/lploc.js>/script> script> var initialized false; function button_callback() { /* (0) check whether were already running face detection */ if(initialized) return; // if yes, then do not initialize everything again /* (1) initialize the pico.js face detector */ var update_memory pico.instantiate_detection_memory(1); // we will use the detecions of the last 1 frame var facefinder_classify_region function(r, c, s, pixels, ldim) {return -1.0;}; var cascadeurl https://raw.githubusercontent.com/nenadmarkus/pico/c2e81f9d23cc11d1a612fd21e4f9de0921a5d0d9/rnt/cascades/facefinder; fetch(cascadeurl).then(function(response) { response.arrayBuffer().then(function(buffer) { var bytes new Int8Array(buffer); facefinder_classify_region pico.unpack_cascade(bytes); console.log(* facefinder loaded); }) }) /* (2) initialize the lploc.js library with a pupil localizer */ var do_puploc function(r, c, s, nperturbs, pixels, nrows, ncols, ldim) {return -1.0, -1.0;}; //var puplocurl ../puploc.bin; var puplocurl https://f002.backblazeb2.com/file/tehnokv-www/posts/puploc-with-trees/demo/puploc.bin fetch(puplocurl).then(function(response) { response.arrayBuffer().then(function(buffer) { var bytes new Int8Array(buffer); do_puploc lploc.unpack_localizer(bytes); console.log(* puploc loaded); }) }) /* (3) get the drawing context on the canvas and define a function to transform an RGBA image to grayscale */ var ctx document.getElementsByTagName(canvas)0.getContext(2d); function rgba_to_grayscale(rgba, nrows, ncols) { var gray new Uint8Array(nrows*ncols); for(var r0; rnrows; ++r) for(var c0; cncols; ++c) // gray 0.2*red + 0.7*green + 0.1*blue grayr*ncols + c (2*rgbar*4*ncols+4*c+0+7*rgbar*4*ncols+4*c+1+1*rgbar*4*ncols+4*c+2)/10; return gray; } /* (4) this function is called each time a video frame becomes available */ var processfn function(video, dt) { // render the video frame to the canvas element and extract RGBA pixel data ctx.drawImage(video, 0, 0); var rgba ctx.getImageData(0, 0, 640, 480).data; // prepare input to `run_cascade` image { pixels: rgba_to_grayscale(rgba, 480, 640), nrows: 480, ncols: 640, ldim: 640 } params { shiftfactor: 0.1, // move the detection window by 10% of its size minsize: 100, // minimum size of a face maxsize: 1000, // maximum size of a face scalefactor: 1.1 // for multiscale processing: resize the detection window by 10% when moving to the higher scale } // run the cascade over the frame and cluster the obtained detections // dets is an array that contains (r, c, s, q) quadruplets // (representing row, column, scale and detection score) dets pico.run_cascade(image, facefinder_classify_region, params); dets update_memory(dets); dets pico.cluster_detections(dets, 0.2); // set IoU threshold to 0.2 // draw detections for(i0; idets.length; ++i) { // check the detection score // if its above the threshold, draw it // (the constant 50.0 is empirical: other cascades might require a different one) if(detsi3>50.0) { var r, c, s; // ctx.beginPath(); ctx.arc(detsi1, detsi0, detsi2/2, 0, 2*Math.PI, false); ctx.lineWidth 3; ctx.strokeStyle red; ctx.stroke(); // // find the eye pupils for each detected face // starting regions for localization are initialized based on the face bounding box // (parameters are set empirically) // first eye r detsi0 - 0.075*detsi2; c detsi1 - 0.175*detsi2; s 0.35*detsi2; r, c do_puploc(r, c, s, 63, image) if(r>0 && c>0) { ctx.beginPath(); ctx.arc(c, r, 1, 0, 2*Math.PI, false); ctx.lineWidth 3; ctx.strokeStyle red; ctx.stroke(); } // second eye r detsi0 - 0.075*detsi2; c detsi1 + 0.175*detsi2; s 0.35*detsi2; r, c do_puploc(r, c, s, 63, image) if(r>0 && c>0) { ctx.beginPath(); ctx.arc(c, r, 1, 0, 2*Math.PI, false); ctx.lineWidth 3; ctx.strokeStyle red; ctx.stroke(); } // At this point, we already know that the human face is detected in webcam. So, Well simply create an image from canvas that is displaying the webcam result in real-time. var can document.getElementsByTagName(canvas)0 var img new Image(); img.src can.toDataURL(image/jpeg, 1.0); // Now, we will send the image to server and process it using PHP. Also, we have to save its path in MySQL database for later use. var data JSON.stringify({ image: img.src }); fetch(save.php, { method: POST, body: data }) .then(function(res){ return res.json(); }) .then(function(data){ return alert( data.message ); }) // This alert statement is a little hack to temporarily stop the execution of script. alert(Face found!); } } } /* (5) instantiate camera handling (see https://github.com/cbrandolino/camvas) */ var mycamvas new camvas(ctx, processfn); /* (6) it seems that everything went well */ initialized true; } /script> /head> body> div> h3>Webcam Face Detection Using JavaScript, PHP, and MySQL by Edopedia.com/h3> p>Click the Start Webcam button below and allow the page to access your webcam./p> p>View Tutorial: a hrefhttps://www.edopedia.com/blog/webcam-face-detection-javascript-php-mysql/ target_blank>https://www.edopedia.com/blog/webcam-face-detection-javascript-php-mysql//a>/p> /div> hr /> p> center> input typebutton valueStart Webcam onclickbutton_callback()> a hrefview.php target_blank>View Saved Images/a> /center> /p> hr /> p> center> canvas width640 height480>/canvas> /center> /p> /body>/html>
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