Anonymous helpers lend a hand

This is precisely what happened when a Good Samaritan couple from Australia, who wished to remain anonymous, came to the Samoa Observer with ...

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You are Welcome at Alcoholics Anonymous

Greetings Fellow Craigslisters, If you are reading this post and you have a problem with drinking alcohol, or you are concerned about your drinking, ...

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Ravens re-sign DB Lardarius Webb to 3-year deal - Adam Schefter; was previously released by team on March 10 (ESPN)

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Empathy on Stage: The Collector and Anonymous in Dublin

Laura Marriott explores Daniel Wade's The Collector and Mark Richardson's Anonymous, two recent productions in Dublin that explore contemporary ...

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Shadow Brokers Group Releases More Stolen NSA Hacking Tools & Exploits

Remember The Shadow Brokers? They are back. A hackers group that previously claimed to have stolen a bunch of hacking tools (malware, zero-day exploits, and implants) created by the NSA and gained popularity last year for leaking a portion of those tools is back. Today, The Shadow Brokers group released more alleged hacking tools and exploits that, the group claims, belonged to "Equation

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Menuet con variazioni

Composer, Anonymous. Key, D major. Piece Style, Baroque. Instrumentation, flute, continuo. Mss Sources, Ms. I, 12. Gieddes samling, Royal Library, ...

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Zeta Oph: Runaway Star

Like a ship plowing through cosmic seas, runaway star Zeta Ophiuchi produces the arcing interstellar bow wave or bow shock seen in this stunning infrared portrait. In the false-color view, bluish Zeta Oph, a star about 20 times more massive than the Sun, lies near the center of the frame, moving toward the left at 24 kilometers per second. Its strong stellar wind precedes it, compressing and heating the dusty interstellar material and shaping the curved shock front. What set this star in motion? Zeta Oph was likely once a member of a binary star system, its companion star was more massive and hence shorter lived. When the companion exploded as a supernova catastrophically losing mass, Zeta Oph was flung out of the system. About 460 light-years away, Zeta Oph is 65,000 times more luminous than the Sun and would be one of the brighter stars in the sky if it weren't surrounded by obscuring dust. The image spans about 1.5 degrees or 12 light-years at the estimated distance of Zeta Ophiuchi. via NASA http://ift.tt/2o860IV

Valentine

Artist: Anonymous. Date: mid 19th century. Medium: Cameo-embossed beige paper, lithography, gold and silver paper die-cut scraps, watercolor, ...

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Easy anonymous button

Hello, I have a working Discourse but I would like for the user to be able to quickly choose weather they want their name on a post or not. the vanilla ...

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WATCH: O'Reilly Ad Factor; Anonymous Account; Fake Front Page

Anonymous Account – Twitter pushed back this week against the Trump administration's request to reveal who was behind an account that has been ...

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Orioles acquire RP Miguel Castro from Rockies for player to be named later or cash; 22 ER over 32.1 career IP (ESPN)

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I have a new follower on Twitter

Cailen Melville
Chess player . I also help defeat cybercriminals. ⚜
San Francisco, CA
https://t.co/iTIk0LkrcB
Following: 2332 - Followers: 4702

April 07, 2017 at 06:04PM via Twitter http://twitter.com/cailenmelville

I have a new follower on Twitter

InfoSec HotSpot
The Latest Regarding Cyber Security https://t.co/CHaVgpsrLO infosechotspot@gmail.com
USA
https://t.co/W48XPTvIt1
Following: 51320 - Followers: 101202

April 07, 2017 at 05:24PM via Twitter http://twitter.com/InfoSecHotSpot

Ravens' 1996 draft class that included Ray Lewis and Jonathan Ogden rated as 10th best in NFL history by ESPN analytics (ESPN)

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WikiLeaks Reveals CIA's Grasshopper Windows Hacking Framework

As part of its Vault 7 series of leaked documents, whistleblowing website WikiLeaks today released a new cache of 27 documents allegedly belonged to the US Central Intelligence Agency (CIA). Named Grasshopper, the latest batch reveals a CLI-based framework developed by the CIA to build "customised malware" payloads for breaking into Microsoft's Windows operating systems and bypassing

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Ravens expected to re-sign CB Lardarius Webb barring any final complications with deal - Jamison Hensley (ESPN)

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ISS Daily Summary Report – 4/06/2017

Flight Day 120 (FD120) Human Research Program (HRP) Collections: The 49S subject performed a fasting blood draw and urine collections. Both samples were stowed in Minus Eighty Degree Celsius Laboratory Freezer for ISS (MELFI) for freezing and storage until their return and analysis. The Biochemical Profile experiment tests blood and urine samples obtained from astronauts before, during, and after spaceflight. Specific proteins and chemicals in the samples are used as biomarkers, or indicators of health. Post-flight analysis yields a database of samples and test results which scientists can use to study the effects of spaceflight on the body. Repository is a storage bank used to maintain biological specimens over extended periods of time and under well-controlled conditions. This repository supports scientific discovery that contributes to our fundamental knowledge in the area of human physiological changes and adaptation to a microgravity environment and provides unique opportunities to study longitudinal changes in human physiology spanning many missions. Electrostatic Levitation Furnace (ELF) Sample Holder Exchange: The crew performed the second part of the ELF Sample Exchange, installing the Sample Holder and Cartridge into the ELF Work Volume. The ELF is an experimental facility designed to levitate/melt/solidify materials by containerless processing techniques using the Electrostatic Levitation method. With this facility, thermophysical properties of high temperature melts can be measured, and solidification from deeply undercooled melts can be achieved. Multi-Omics Mouse Preparations: In preparation for the JAXA Rodent Research experiment hardware launching on SpaceX-11, the crew set up the CO2 Valve Unit and performed a checkout.  Potable Water Dispenser (PWD) Relocate Postponed:  The PWD was scheduled to be relocated today but the activity was postponed.  The crew spent time yesterday and today looking for an adapter needed for the activity but were unable to locate it.  Ground teams are discussing work arounds to allow the relocation to occur without using the adapter. Today’s Planned Activities All activities were completed unless otherwise noted. URAGAN. Observation and photography EKON-M. Observations and photography Lighting Effects Sleep Log Entry HRF Generic Urine Collection HRF Generic Saliva Collection HRF Generic Frozen Blood Collection HRF Generic Sample MELFI Insertion Operations HRF Generic Refrigerated Centrifuge Spin NEUROIMMUNITET. Saliva sample collection Regenerative Environmental Control and Life Support System (ECLSS) Recycle Tank Drain Health Maintenance System (HMS) Stow Electrostatic Levitation Furnace (ELF) Experiment Sample Holder Install Regenerative Environmental Control and Life Support System (ECLSS) Recycle Tank Drain Part 2 LBNP Training  In Flight Maintenance (IFM) Waste and Hygiene Compartment (WHC) Full Fill Electrostatic Levitation Furnace(ELF) Sample Removal Acoustic Dosimeter Setup Day 3 Soyuz 732 Stowage Ops for Return. Electrostatic Levitation Furnace (ELF) Sample Cartridge 2 Install Electrostatic Levitation Furnace (ELF) Slit Cover stow Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill On-orbit Hearing Assessment using EARQ IDENTIFICATION. Copy ИМУ-Ц micro-accelerometer data to laptop HRF Generic Sample MELFI Retrieval Insertion Operations JEM Common Gas Support Equipment (CGSE) Gas Supply Start Pre-Multi-Omics Mouse Item Gathering Recharging Soyuz 733 Samsung PC Battery (if charge level is below 80%) CO2 Vlv Unit Setup IDENTIFIKATSIYA. Copy ИМУ-Ц Micro-Accelerometer Data to HDD for return Combustion Integrated Rack (CIR) Alignment Guide Installation CO2 Vlv Unit Checkout Multi-purpose Small Payload Rack (MSPR) /Group Combustion Module (GCM) Component Deactivation Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill Recharging Soyuz 732 Samsung PC Battery (if charge level is below 80%) JEM Common Gas Support Equipment Gas Supply Stop Hardware prepack for return and disposal on Soyuz 732 Glove Box Panel Closeout Manufacturing Device Print Removal, Clean and Stow Network Monitoring System (NMS) Laptop Battery Swap VEG-03 Wick Open Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill Separation of ЕДВ using Separation Unit [УС] Soyuz 732 Transfer Ops Galley Potable Water Dispenser (PWD) Installation [Aborted] Space Headaches – Weekly Questionnaire CALCIUM. Bioekololgiya Cases: Photography, Processing, and Photo Downlink, Pre-pack for Return Regenerative Environmental Control and Life Support System (ECLSS) Recycle Tank Fill Part 3 48S US Prepack Trash Staging Cleanout HRF Generic Sample MELFI Insertion Operations INTERACTION-2. Experiment Ops OA7 Trash Pregather Galley Potable Water Dispenser (PWD) Installation Part 2 Terminate Soyuz 733 Samsung PC Battery Recharge (if necessary) INTERACTION-2. Experiment Ops Preventive maintenance of MRM1 АСП Hatch Sealing Mechanism and Soyuz 732 hatch Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill HRF Generic Sample MELFI Retrieval Insertion Operations Completed Task List Items Galley Rack Power Source Swap (From aborted Galley Potable Water Dispenser (PWD) Installation Activity) Portable Water Dispenser – TOCA (Total Organic Carbon Analyzer) Water Sample Collection & Analysis Portable Water Dispenser – Environmental Health System (EHS) Coliform Water Detection JLP Cleanup and Reconfiguration Ground Activities All activities were completed unless otherwise noted. Galley Rack Power Source Swap Support – Safing and Power/De-power Assistance    Three-Day Look Ahead: Friday, 04/07: Crew off duty Saturday, 04/08: Crew off duty, housekeeping Sunday, 04/09: 49S Crew Emergency Roles/Responsibilities review, Change of Command QUICK ISS Status – Environmental Control Group:   Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off           [СКВ] 2 – SM Air Conditioner System (“SKV2”) On Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Operate Major Constituent Analyzer (MCA) Node 3 Operate Oxygen Generation Assembly (OGA) Process Urine Processing Assembly (UPA) Process Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up  

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I have a new follower on Twitter

Iqbal Azad
I am the creator of the record label @ThinkersRave. A music channel like @Vevo @billboard @bbcmusic where we post new #musicvideo every friday.
Manhattan, NY
https://t.co/pPb3IlO5Fc
Following: 1578 - Followers: 927

April 07, 2017 at 02:39AM via Twitter http://twitter.com/TheIqbalAzad

Castle Eye View

The best known asterism in northern skies, The Big Dipper is easy to recognize, even when viewed upside down, though some might see a plough or wagon. The star names and the familiar outlines appear framed in the ruined tower walls of the French Chateau du Morimont if you just slide your cursor over the image or follow this link. Dubhe, alpha star of the dipper's parent constellation Ursa Major is at the lower left. Together with beta star Merak the two form a line pointing the way to Polaris and the North Celestial Pole, hidden from view by the stones. Since the image was captured on March 30, you can follow a line from dipper stars Phecda and Megrez to spot the faint greenish glow of Comet 41P/Tuttle-Giacobini-Kresak below center, still within the castle eye view. The periodic comet made a remarkable close approach to planet Earth on April 1. via NASA http://ift.tt/2oFThzz

2017 Jupiter Opposition

On April 7, 2017, Jupiter and the sun will be positioned on opposite sides of the Earth in what is known as a "Jupiter opposition." Jupiter's closest approach to Earth for the year always falls on or near this Jupiter's opposition date. In 2017, Jupiter comes closest to Earth one day after its opposition date, on April 8, coming to within 414 million miles (666 million kilometers) of Earth. If Jupiter and Earth had perfectly circular orbits, closest approach would occur at the same time as opposition. However, since Jupiter and Earth both have elliptical orbits, the closest approach is not aligned with opposition, and varies from year to year.

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U.S. Trade Group Hacked by Chinese Hackers ahead of Trump-Xi Trade Summit

Researchers have uncovered a Chinese cyber-espionage against the United States ahead of the trade summit on Thursday between US President Donald Trump and China's President Xi Jinping. According to a new report published today by Fidelis Cybersecurity firm, the Chinese APT10 hacking group implanted a piece of malware on the "Events" page of the US National Foreign Trade Council (NFTC) website

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[FD] CSRF/stored XSS in WordPress Firewall 2 allows unauthenticated attackers to do almost anything an admin can (WordPress plugin)

Details ================ Software: WordPress Firewall 2 Version: 1.3 Homepage: http://ift.tt/2odN5hx Advisory report: http://ift.tt/2o1qq6f CVE: Awaiting assignment CVSS: 5.8 (Medium; AV:N/AC:M/Au:N/C:P/I:P/A:N) Description ================ CSRF/stored XSS in WordPress Firewall 2 allows unauthenticated attackers to do almost anything an admin can Vulnerability ================ HTML is not escaped and there is no CSRF prevention, meaning attackers can put arbitrary HTML content onto the settings page. Proof of concept ================ Visit the following page, click on the submit button, then visit the plugin’s options page:

<script>alert(1)</script>\">

In a real attack, forms can be submitted automatically and spear-phishing attacks can be convincing. Mitigations ================ Disable the plugin until a new version is released that fixes this bug. Disclosure policy ================ dxw believes in responsible disclosure. Your attention is drawn to our disclosure policy: http://ift.tt/1B6NWzd Please contact us on security@dxw.com to acknowledge this report if you received it via a third party (for example, plugins@wordpress.org) as they generally cannot communicate with us on your behalf. This vulnerability will be published if we do not receive a response to this report with 14 days. Timeline ================ 2016-12-23: Discovered 2017-03-16: Reported to vendor by email 2017-04-04: Vendor could not be contacted Discovered by dxw: ================ Tom Adams Please visit security.dxw.com for more information.

Source: Gmail -> IFTTT-> Blogger

ISS Daily Summary Report – 4/05/2017

Synchronized Position Hold, Engage, Reorient, Experimental Satellites (SPHERES) Universal Docking Port (UDP): The crew completed a test run for the SPHERES UDP payload. They loaded the test software and performed the session with ground support staff direction. Objectives of the UDP session are to demonstrate a reliably successful docking through running multiple, repeatable docking maneuvers using both global metrology and docking port cameras; perform joint maneuvers of docked satellites using the thrusters from two satellites to demonstrate controllability; and test an algorithm for docking to a satellite which is tumbling in a slow, known manner. The addition of the Docking Ports is a critical upgrade to the SPHERES facility aboard the ISS. With the new ability to dock and undock, SPHERES provides a test bed to address many of the challenges of combining autonomous spacecraft. Mated spacecraft can assemble complex systems in orbit or combine sensors and actuators for satellite servicing and repurposing missions. The SPHERES-UDP enables testing of complex tasks through optimal and adaptive control, autonomous decision-making processes, and real-time image processing. Electrostatic Levitation Furnace (ELF) Sample Holder Exchange: The crew performed the first of two days of operations in support of the JAXA ELF Sample exchanges in the Multi-Purpose Small Payload Rack-2 (MSPR2) facility.  They removed the sample holder and installed the new cartridge into the holder. The ELF is an experimental facility designed to levitate/melt/solidify materials by containerless processing techniques using the Electrostatic Levitation method. With this facility, thermophysical properties of high temperature melts can be measured, and solidification from deeply undercooled melts can be achieved.  Story Time From Space Light Demo: The crew narrated and recorded a video to demonstrate the spectrum of the light from the sun and the attenuation of the light intensity as the sun is viewed through the atmosphere. Story Time From Space combines science literacy outreach with simple demonstrations recorded aboard the ISS. Crew members read five science, technology, engineering and mathematics-related childrens’ books in orbit, and complete simple science concept experiments. Crew members videotape themselves reading the books and completing demonstrations. Video and data collected during the demonstrations are downlinked to the ground and posted in a video library with accompanying educational materials. The narrated demonstration is based on the childrens’ books Max Goes to Mars, The Wizard Who Saved the World, and Max Goes to Jupiter. Multi-Omics Mouse Preparations: In preparation for the JAXA Rodent Research experiment hardware launching on SpaceX-11 (SpX-11), the crew installed the Glove Box Panel on the Kobairo Rack front in the Japanese Experiment Module (JEM). Following installation, the attachment points for the Working Table were marked with Kapton tape for easier operations on SpX-11.  In Flight Maintenance (IFM) Crew Quarters (CQ) Overhead Cleaning: In preparation for departure from the ISS next week, the CDR cleaned his CQ intake and exhaust ducts as well as fans and airflow sensors while targeting areas behind applicable panels.   Extravehicular Mobility Unit (EMU) Maintenance: During today’s post Extravehicular Activity (EVA) EMU suit maintenance, a step to switch the suits to battery power from Service and Cooling Umbilical (SCU) power was missed. While powering up for a cooling loop scrub, both EMU 3006 and 3008 were configured for station power during the power up sequence rather than battery power. Powering EMUs from battery power is to protect from power spikes that may occur when the DC to DC converter is powered. During the activity, there were no DC-DC converter trips, no EMU current limiter trips and nominal suit data was observed immediately after power up on both suits. Ground teams are evaluating further for any unknown impacts.  The cooling loop scrub was completed with no further issues. Today’s Planned Activities All activities were completed unless otherwise noted. Columbus Module Light Unit 3 Lamp Housing Assembly Remove and Replace. Test video recording for RT TV channel Prep of personal data for return Preparation of Reports for Roscosmos Web Site and Social Media URAGAN. Observation and photography EKON-M. Observations and photography Lighting Effects Sleep Log Entry – Subject Acoustic Dosimeter Reminder HRF Generic Urine Collection NEUROIMMUNITET. Saliva Sample. Psychological Test HRF Generic Sample MELFI Insertion Operations KORREKTSIYA. NEUROIMMUNITET. Blood Collection. SPHERES Battery Swap Combustion Integrated Rack Alignment Guide Removal Acoustic Dosimeter Setup Day 2 XF305 Camcorder Setup Verification of ИП-1 Flow Indicator Position BIOCARD. Experiment Ops. Electrostatic Levitation Furnace (ELF) Sample Holder Removal NEUROIMMUNITET. Psychological Test Extravehicular Mobility Unit (EMU) Cooling Loop Maintenance Scrub Initiation Electrostatic Levitation Furnace (ELF) Sample Cartridge 2 Install OTKLIK. OTKLIK memory buffer clearing MERLIN 2 Desiccant Swap Health Maintenance System (HMS) EpiPen Ziplock Modification ISS Crew departure preparation Pre-Multi-Omics Mouse Item Gathering Glove Box Panel Setup and Working Table position marking SPHERES Battery Stow HRF Generic Saliva Collection Setup PROFILAKTIKA-2. Copy Data to Laptop Export MBI Experiment Data to a memory card for return Extravehicular Mobility Unit (EMU) Post Scrub Cooling Loop Water (H2O) Sample Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill Preparations to connect the AstroPi Vis to the ISS Joint Station LAN. Extravehicular Mobility Unit (EMU) Cooling Loop Maintenance Iodination Extravehicular Mobility Unit (EMU) Conductivity Test SPHERES File Delete Environmental Health System (EHS) – Formaldehyde Monitoring Kit (FMK) Stow Operation ESA ACTIVE DOSIMETER MOBILE UNIT SWAP AstroPi status check SPHERES Test Session Setup Cycle 14.1 Laptop & CD Audit EVA Extravehicular Mobility Unit (EMU) Cooling Loop Scrub Deconfiguration Google Street View Cupola Photo Operations In Flight Maintenance (IFM) Crew Quarters (CQ) Overhead Cleaning On MCC Go Removal of unit 800А (А103) Replacement of SM 800А Battery Modules No.2, No.3, Operator StoryTime from Space GoPro video transfer Story Time from Space Light Demo On MCC Go Removal of 800А unit (А102) Replacement of SM 800А Battery Modules No.2, No.3, Operator SPHERES Docking Port Test Run Story Time From Space Historical Photo Meteor Hard Drive Swap and LED Cover Reinstallation of unit 800А from position А102 to А103 Replacement of SM 800А Battery Modules No.2, No.3, Operator Reinstallation of unit 800А from position А103 to А102 INTERACTION-2. Experiment Ops […]

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Microsoft Finally Reveals What Data Windows 10 Collects From Your PC

Since the launch of Windows 10, there has been widespread concern about its data collection practices, mostly because Microsoft has been very secretive about the telemetry data it collects. Now, this is going to be changed, as Microsoft wants to be more transparent on its diagnostics data collection practices. Till now there are three options (Basic, Enhanced, Full) for Windows 10 users to

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Orioles Video: Chris Davis crushes solo shot to left-center an inning after Adam Jones hit two-run blast in 3-1 win over Blue Jays (ESPN)

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Blog owner not liable for anonymous defamatory online comments

The ECHR held that the Swedish authorities' refusal to hold the owner of the blog liable for the anonymous defamatory online comment did not violate ...

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TIL 038 : The Bible And Alcoholics Anonymous (feat. Mark Shaw)

On this edition of Truth in Love, Dr. Lambert talks with Mark Shaw about how Christians should respond to Alcoholics Anonymous. Mark discusses the ...

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Police: Anonymous tip leads to arrest in Scranton hit-and-run

On March 31, police received an anonymous tip claiming who the vehicle in the incident belonged to, and that the side rear view mirror to the vehicle ...

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ALCOHOLICS ANONYMOUS 208-235-1444 AL-ANON 208-232-2692

ALCOHOLICS ANONYMOUS 208-235-1444 AL-ANON 208-232-2692.

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No More Ransom — 15 New Ransomware Decryption Tools Available for Free

No More Ransom, so is the Ransomware Threat. Launched less than a year ago, the No More Ransom (NMR) project has increased its capacity with new partners and new decryption tools added to its now global campaign to combat Ransomware. Started as a joint initiative by Europol, the Dutch National Police, Intel Security and Kaspersky Lab, No More Ransom is an anti-ransomware cross-industry

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Dueling 2-Rd Mock Draft: Mel Kiper gives Ravens two UCLA prospects, pass-rusher Takkarist McKinley at No. 16, CB Fabian Moreau at No. 47 (ESPN)

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Ravens GM Ozzie Newsome says \"high probability\" team adds free agent before draft; C Nick Mangold currently visiting (ESPN)

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Ravens hosting former Clemson WR Mike Williams and ex-Washington WR John Ross for pre-draft visits Wednesday (ESPN)

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ISS Daily Summary Report – 4/04/2017

Return minus 15 (R-15) Human Research Program (HRP) Collections: The 48S returning crewmember performed a fasting blood draw followed by urine collections. Both blood and urine samples were stowed in Minus Eighty Degree Celsius Laboratory Freezer for ISS (MELFI) for freezing and storage for return and analysis. The Biochemical Profile experiment tests blood and urine samples obtained from astronauts before, during, and after spaceflight. Specific proteins and chemicals in the samples are used as biomarkers, or indicators of health. Post-flight analysis yields a database of samples and test results which scientists can use to study the effects of spaceflight on the body. The repository is a storage bank used to maintain biological specimens over extended periods of time and under well-controlled conditions. This repository supports scientific discovery that contributes to our fundamental knowledge in the area of human physiological changes and adaptation to a microgravity environment and provides unique opportunities to study longitudinal changes in human physiology spanning many missions. Habitability: The crew completed two Habitability activities, both the fifth in the series.  The first activity was a walk-through video of areas used for recreation activities, explaining what activities are performed and where, and focusing on considerations for designers of future vehicles. The second activity was a Narrated Task Video of the Node 3 ventilation cleaning, capturing details such as volume needed to perform task, vehicle planning considerations, and systems interface issues, as well as any other human factors concerns. The Habitability investigation collects observations about the relationship between crewmembers and their environment on the ISS. Observations can help spacecraft designers understand how much habitable volume is required, and whether a mission’s duration impacts how much space crew members need.  Lighting Effects Meter Reading: The crew set up and configured the Light Meter hardware and took readings in the Node 3 and US Lab.  Both modules still use the legacy General Luminaire Assembly (GLA), while the lights in Node 1 have been upgraded to the Solid State Lighting Assemblies (SSLAs). The Lighting Effects experiment hopes to better quantify and qualify how lighting can effect habitability of spacecraft. The light bulbs on the ISS are being replaced with a new system designed for improved crew health and wellness. The Lighting Effects investigation studies the impact of the change from fluorescent light bulbs to solid-state light-emitting diodes (LEDs) with adjustable intensity and color and aims to determine if the new lights can improve crew circadian rhythms, sleep, and cognitive performance. Results from this investigation also have major implications for people on Earth who use electric lights.  Node 2 HMU 220 Power Cable Re-route: Today the crew completed re-routing an existing power cable (HMU 220) from Node 2 to a previously routed wire harness. HMU 220 previously provided power to the Node 2 Zenith berthing port through the HTV Node 2 Jumper. The power cable was routed from the Node 2 Forward Endcone toward  the Node 2 Deck Crew Quarter Standoff and mated to wire harness W8553 to support a redundant power feed for the previously installed Node 1 Galley Rack. During the HMU 220 task, Shell Heater temperature sensor 1B in Pressurized Mating Adapter (PMA) 2 failed high. Wire harness HMU 671, adjacent to HMU 220, provides data routing for the failed sensor. The crew was directed to inspect the harness for damage but none was reported. There is sufficient redundancy on shell heater 1A. Grounds teams are reviewing telemetry. On Board Training (OBT) Soyuz Descent Drill:  In preparation for departure from the ISS scheduled for next Monday, April 10th, the 48S Crew completed this nominally planned descent drill.  N3 Deck Starboard Intermodule Ventilation (IMV) Fan Inlet Cleaning: The crew cleaned this location to remove Foreign Object Debris (FOD) from IMV fan inlets and silencers.  Today’s Planned Activities All activities were completed unless otherwise noted. Soyuz 732 Stowage Ops Preparation of Reports for Roscosmos Web Site and Social Media URAGAN. Observation and photography EKON-M. Observations and photography Lighting Effects Sleep Log Entry Acoustic Dosimeter Reminder ARED Photo/TV Reminder Reminder HRF Generic Frozen Blood Collection HRF Generic Urine Collection HRF Generic Frozen Blood Collection VHF-2 Emergency Communication Check Out from 49S over US Ground Sites SPHERES Battery Swap EHS Total Organic Carbon Analyzer (TOCA) Water Recovery System (WRS) Sample Analysis Acoustic Dosimeter Setup Day 1 HRF Generic Refrigerated Centrifuge Spin HRF Generic Sample MELFI Insertion Habitability Walk-through Video ISS Crew departure preparation Soyuz 732 Descent OBT Photography of Glass on SM Windows No.1,12 and ВЛ2 in in DC1 Node 2 Power Cable (HMU 220) Reroute SPHERES Battery Swap Vascular Echo Flashdrive Install Closing Shutters on windows 6, 8, 9, 12, 13, 14.Note 6 Lighting Effects Light Meter Readings Alternate 1 Maintenance activation of Atmosphere Purification System Emergency Vacuum Valves [АВК СОА] from the Spares Kit (СМ1РО_3_321_1, bag II-1/256-1, cover for [АВК] (007223R))) USOS Window Shutter Close DAN. Experiment Ops HRF Generic Urine Collection In Flight Maintenance (IFM) Node 3 Deck Starboard Intermodule Ventilation (IMV) Cleaning Brine transfer to Progress 435 Rodnik H2O Tank 1, flushing connector B1 Habitability Narrated Task Video Setup Node 2 Power Cable (HMU 220) Rerouting Soyuz 732 СУД Test prior to undocking Soyuz 732 [АСУ] Activation Habitability Narrated Task Video End – Subject External Wireless Instrumentation System (EWIS) Network Control Unit (NCU) Power On KORREKTSIYA. NEUROIMMUNITET. Experiment Rodent Research 4 Clean up 1    Vascular Echo Software Transfer EHS Total Organic Carbon Analyzer (TOCA) Sample Data Record External Wireless Instrumentation System (EWIS) Network Control Unit (NCU) Power Off Dose Tracker Data Entry Subject NEUROIMMUNITET Completed Task List Items Manufacturing Device Print Removal, Clean and Stow Remove Lamp Housing Assembly NOD3FO2 and Replace with Light  Ground Activities All activities were completed unless otherwise noted. Node 2 (N2) Power Cable re-routing support  Three-Day Look Ahead: Wednesday, 04/05: Galley PWD install, EMU loop scrub, Crew Quarters cleaning, crew departure prep Thursday, 04/06: Rodent Research inventory, Google Street View image acquisition, 48S prepack, VEG03 install Friday, 04/07: Crew off duty QUICK ISS Status – Environmental Control Group:   Component Status Elektron On Vozdukh Manual […]

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I have a new follower on Twitter

TrooMobile
TrooMobile : We build mobile solutions! https://t.co/1EnkfkSxu7 https://t.co/AxD8uHwWgU 949.281.4970 hi@troomobile.com
Orange County, CA
http://troomobile.com
Following: 2407 - Followers: 2700

April 05, 2017 at 06:40AM via Twitter http://twitter.com/troomobile

Millions Of Smartphones Using Broadcom Wi-Fi Chip Can Be Hacked Over-the-Air

Millions of smartphones and smart gadgets, including Apple iOS and many Android handsets from various manufacturers, equipped with Broadcom Wifi chips that support Cisco Centralized Key Management (CKKM) Fast Secure Roaming feature are vulnerable to over-the-air hijacking without any user interaction. Just yesterday, Apple rushed out an emergency iOS 10.3.1 patch update to address a serious

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This book consists of a compilation of the best anonymous quotes covering various topics. These range from expectations to excellence and.

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Tim Berners-Lee, Inventor of the Web, Wins $1 Million Turing Award 2016

Sir Tim Berners-Lee — the inventor of the World Wide Web — has won this year's A.M. Turing Award, which is frequently described as the "Nobel Prize of Computing," by the Association for Computing Machinery (ACM). Turing Award is named after Alan Mathison Turing, the British mathematician and computer scientist who was a key contributor to the Allied cryptanalysis of German Enigma cipher and

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NFL Free Agency: C Nick Mangold visiting with Ravens on Tuesday and Wednesday - Jamison Hensley (ESPN)

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I have a new follower on Twitter

Extreme Networks
The latest news and updates from Extreme Networks, delivering software-driven networking solutions that help IT departments deliver better business outcomes.
San Jose, California
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Following: 6369 - Followers: 11338

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Ravens invested heavily on defense, but pass-rusher remains atop team's priorities; need big-time player to get after QB - Jamison Hensley (ESPN)

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Anonymous Grammar Vigilante Corrects Mistakes On Signs

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Ravens trade DT Timmy Jernigan and 2017 3rd-round pick (No. 99) to Eagles for 3rd-rounder (No. 74) this year (ESPN)

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Update Your Apple Devices to iOS 10.3.1 to Avoid Being Hacked Over Wi-Fi

Less than a week after Apple released iOS 10.3 with over 100 bug fixes and security enhancements; the company has just pushed an emergency patch update – iOS 10.3.1 – to addresses a few critical vulnerabilities, one of which could allow hackers to "execute arbitrary code on the Wi-Fi chip." The vulnerability, identified as CVE-2017-6975, was discovered by Google's Project Zero staffer Gal

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Allow anonymous users to subscribe

I think it would make sense to let anaonymous users to subscribe as well.

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Google just discovered a dangerous Android Spyware that went undetected for 3 Years

An Android version of one of the most sophisticated mobile spyware has been discovered that remained undetected for at least three years due to its smart self-destruction capabilities. Dubbed Chrysaor, the Android spyware has been used in targeted attacks against activists and journalists mostly in Israel, but also in Georgia, Turkey, Mexico, the UAE and other countries. Chrysaor espionage

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ISS Daily Summary Report – 4/03/2017

EXpedite PRocessing of Experiments to Space Station (EXPRESS) Rack Locker Relocation: Following the successful completion of the Rodent Research-4 experiment during SpaceX-10, this morning the crew reconfigured EXPRESS Racks 1 and 2 to their nominal configuration for upcoming payload operations.  Programmable Isolation Mount (PIM): The crew installed the PIM into EXPRESS Rack 7 in the US Lab. The Controlled Dynamics Locker (CDL) is an EXPRESS locker insert with a programmable isolation mount inside. The research experiment is mounted to the isolated platform interface inside the locker insert. The isolation platform provides the research experiment with a broadband acceleration environment below 10µg-rms from 0.01Hz to 200Hz on ISS. It also allows for programmable variations of that dynamic acceleration environment independently in each axis. Microgravity research in areas such as protein crystal growth, fluid physics, plant biology and horticulture, stem cell research, cell/tissue culturing and other microstructure studies focusing on the intricacies of cell functioning and mechanisms would benefit from utilizing the customizable features of the PIM. Manufacturing Device (MD) Operations: The crew removed and replaced (R&R) the MD Feedstock Canister, Extruder, and Print Tray. The Manufacturing Device -Additive Manufacturing Facility (AMF) enables the production of components on the ISS for both NASA and commercial objectives. Parts, entire experiments, and tools can be created on demand utilizing the AMF that is installed into an Express Rack locker location. The AMF is capable of producing parts out of a wide variety of thermopolymers including engineered plastics.  ISS Reboost: The ISS performed a nominal reboost using the Service Module (SM) main engine thrusters.  The reboost was to set up planned conditions for  48S landing on April 10 and 50S launch on April 20. Portable Emergency Provisions (PEPS) Inspection: The crew completed this regularly scheduled maintenance to inspect Portable Fire Extinguishers (PFEs), Portable Breathing Apparatus (PBAs) and Extension Hose Tee Kits (EHTKs). They will also performed 180-day mask harness maintenance. Node 1 (N1) Starboard Aft Intermodule Ventilation (IMV) Fan Inlet Cleaning: The crew completed cleaning this location to remove Foreign Object Debris (FOD) from IMV fan inlets and silencers. Today’s Planned Activities All activities were completed unless otherwise noted. KORREKTSIA. Collection of Blood Samples [Aborted] KORREKTSIA. Hand over to USOS for placement into MELFI [Aborted] Environmental Control and Life Support System (ECLSS) Portable Emergency Provisions (PEPS) Inspection Environmental Health System (EHS) Acoustic Dosimeter Operations – Setup Dosimeter for Static Measurement ISS HAM Service Module Pass [Aborted] At Home In Space Video USOS Window Shutter Close KORREKTSIA. Taking food and liquids (medicine) registration in flight log [Aborted] Closing Window Shutters # 6,8,9,12,13,14. Note 5 FAGEN. Deactivate [“МСК] №5 kit FAGEN. Photography of kits SM Ventilation Subsystem Preventive Maintenance. Group А In Flight Maintenance (IFM) Node 1 Aft Starboard Intermodule Ventilation (IMV) Fan Cleaning On MCC GO Drain water from Progress №435 [БВ1] tank. Compress bladder of Progress  №435 [БВ1] tank Photography of panels 131, 135 to find a place for [ЕДВ-РП] location EXPRESS Rack 1 Locker Move MATRYOSHKA-R. Photography of “Protection shutter” experiment location EXPRESS Rack 2 Locker Move EXPRESS Rack 1 Locker Install Environmental Health System (EHS) – Rad Detector Rotate EXPRESS Rack 2 Locker Install LBNP simulation (PRELIMINARY) LBNP Exercise (PRELIMINARY) – (Operator) Google Street View Q&A Interview Manufacturing Device Print Removal, Clean and Stow Programmable Isolation Mount Hardware Locate Urine Processing Assembly (UPA) Separator Plumbing Assembly (SPA) Contingency Water Container-Iodine (CWC-I) Swap VEG-03 MWA Preparation PIM Locker Insert Install Water Recovery System Waste Water Tank Drain Termination Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill [Aborted] VEG-03 Experiment Install HRF Generic Urine Collection Setup Stow equipment in Soyuz №732 HRF Generic Frozen Blood Collection Setup SM Ventilation Subsystem Preventive Maintenance. Group А Wet Lab Kit Resupply Preventive Maintenance of FS1 Laptop Recharge IRIDIUM phone of Soyuz №732- setup and start of charging (ФГБ1ПГО_2_224_1, 0.5 CTB 1017, soft container 00044322R) Monthly smart switch [БРИ] cleaning and audit of cables Node 2 HMU220 Procedure Review Recharge IRIDIUM phone of Soyuz №732 – check battery level Recharge IRIDIUM phone of Soyuz №732- switch off charging, tear down (store at ФГБ1ПГО_2_224_1, 0.5 CTB 1017, soft container 00044322R) Crew Departure Preparations for Return to Earth Node 2 Cable Routing (HMU 220) Conference Space Automated Bioproduct Lab 2 Hard Drive Swap Medical Consumables Tracking Manual System Scan Story Time From Space Flash Drive Buoyancy Video Transfer Alpha Magnetic Spectrometer HRDL Cable Move Two Environmental Health System (EHS) – Formaldehyde Monitoring Kit (FMK) Deployment Operations NAPOR-mini RSA. Cleaning Onboard Memory Storage БЗУ-М vents Environmental Health System (EHS) Grab Sample Container (GSC) Sampling Operations Fit check in KAZBECK suit Compression of Progress №435 tank [БВ1]. Concluding ops Multi-purpose Small Payload Rack (MSPR) /Group Combustion Module (GCM) Component Activation Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill SPHERES Battery Setup                                  Completed Task List Items Airlock Deconfiguration  [Completed GMT 91] GOOGLE JEM Photo [Completed GMT 92] ESA PAO Hands of Air France [Completed GMT 92] Systems Operations Data File (SODF) Emergency Book Update [Completed GMT 92] Deconfigure and stow tools and hardware from US EVA 41 [Completed GMT 92] HRF Hardware Trash [Completed GMT 92] Network Monitoring System (NMS) Reload [Completed GMT 92] Replace KTO [Completed GMT 93] Ground Activities All activities were completed unless otherwise noted. PIM installation support Three-Day Look Ahead: Tuesday, 04/04: Soyuz OBT, N2 power cable rerouting for N1 Galley Rack, Habitability experiment Wednesday, 43/05: Galley PWD install, EMU loop scrub, Crew Quarters cleaning, crew departure prep Thursday, 04/06: Rodent Research inventory, Google Street View image acquisition, 48S prepack, VEG03 install QUICK ISS Status – Environmental Control Group:   Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off           [СКВ] 2 – SM Air Conditioner System (“SKV2”) On Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Operate Major Constituent Analyzer (MCA) Node 3 Operate Oxygen […]

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Hackers stole $800,000 from ATMs using Fileless Malware

Hackers targeted at least 8 ATMs in Russia and stole $800,000 in a single night, but the method used by the intruders remained a complete mystery with CCTV footage just showing a lone culprit walking up to the ATM and collecting cash without even touching the machine. Even the affected banks could not find any trace of malware on its ATMs or backend network or any sign of an intrusion. The

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Trail Blazer

Beautiful Stories From Anonymous People #55 April 4, 2017. It's a story like something out of a surreal American novel, with wealth and poverty ...

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Food Addicts in Recovery Anonymous(FA)

Eventbrite - Food Addicts in Recovery Anonymous(FA) presents Food Addicts in Recovery Anonymous(FA) - Friday, 14 April 2017 | Friday, ...

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The War Room – Episode 32 – Vandalholics Anonymous

The official podcast for right-wing veterans. In this episode, Violent Vanzetti fills in for Psycho Sacco as the Secretary of War, and the joint chiefs go ...

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(\u25B6)Manny Machado dives down line for spectacular grab and still manages to throw out runner from knees (ESPN)

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\"A Trumbo jumbo!\" Orioles DH crushes walk-off HR in bottom of 11th for 3-2 Opening Day win over Blue Jays - #SCtop10 (ESPN)

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Beware! Views On New Feature Facebook Stories Feature Won't Be Anonymous

Your days of anonymously creeping on Facebook are over, that is if you decide to starting viewing your friends "Stories". Here's what you need to ...

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Android Beats Windows to Become World's Most Popular Operating System

It's an impressive milestone for Google — For the first time in decades, Android has been crowned as the world's most popular operating system in terms of Internet usage, knocking Microsoft Windows off the top spot. According to a new report from web traffic analytics firm StatCounter, Google's Android is the most popular operating system worldwide in terms of total internet usage across

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Ravens schedule visit with Temple LB Haason Reddick - Jamison Hensley; possible first-round pick (ESPN)

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Buddy Montana for Ballers Anonymous

This is part of a series of characters, logotypes and other illustrations that has been done for Ballers Anonymous. Check them out on Instagram ...

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Orioles: Seth Smith bats leadoff in opener vs. Blue Jays followed by Adam Jones, Manny Machado; Welington Castillo (6th), Hyun Soo Kim (7th) (ESPN)

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Facial landmarks with dlib, OpenCV, and Python

Last week we learned how to install and configure dlib on our system with Python bindings.

Today we are going to use dlib and OpenCV to detect facial landmarks in an image.

Facial landmarks are used to localize and represent salient regions of the face, such as:

• Eyes
• Eyebrows
• Nose
• Mouth
• Jawline

Facial landmarks have been successfully applied to face alignment, head pose estimation, face swapping, blink detection and much more.

In today’s blog post we’ll be focusing on the basics of facial landmarks, including:

1. Exactly what facial landmarks are and how they work.
2. How to detect and extract facial landmarks from an image using dlib, OpenCV, and Python.

In the next blog post in this series we’ll take a deeper dive into facial landmarks and learn how to extract specific facial regions based on these facial landmarks.

To learn more about facial landmarks, just keep reading.

Looking for the source code to this post?
Jump right to the downloads section.

Facial landmarks with dlib, OpenCV, and Python

The first part of this blog post will discuss facial landmarks and why they are used in computer vision applications.

From there, I’ll demonstrate how to detect and extract facial landmarks using dlib, OpenCV, and Python.

Finally, we’ll look at some results of applying facial landmark detection to images.

What are facial landmarks?

Figure 1: Facial landmarks are used to label and identify key facial attributes in an image (source).

Detecting facial landmarks is a subset of the shape prediction problem. Given an input image (and normally an ROI that specifies the object of interest), a shape predictor attempts to localize key points of interest along the shape.

In the context of facial landmarks, our goal is detect important facial structures on the face using shape prediction methods.

Detecting facial landmarks is therefore a two step process:

• Step #1: Localize the face in the image.
• Step #2: Detect the key facial structures on the face ROI.

Face detection (Step #1) can be achieved in a number of ways.

We could use OpenCV’s built-in Haar cascades.

We might apply a pre-trained HOG + Linear SVM object detector specifically for the task of face detection.

Or we might even use deep learning-based algorithms for face localization.

In either case, the actual algorithm used to detect the face in the image doesn’t matter. Instead, what’s important is that through some method we obtain the face bounding box (i.e., the (x, y)-coordinates of the face in the image).

Given the face region we can then apply Step #2: detecting key facial structures in the face region.

There are a variety of facial landmark detectors, but all methods essentially try to localize and label the following facial regions:

• Mouth
• Right eyebrow
• Left eyebrow
• Right eye
• Left eye
• Nose
• Jaw

The facial landmark detector included in the dlib library is an implementation of the One Millisecond Face Alignment with an Ensemble of Regression Trees paper by Kazemi and Sullivan (2014).

This method starts by using:

1. A training set of labeled facial landmarks on an image. These images are manually labeled, specifying specific (x, y)-coordinates of regions surrounding each facial structure.
2. Priors, of more specifically, the probability on distance between pairs of input pixels.

Given this training data, an ensemble of regression trees are trained to estimate the facial landmark positions directly from the pixel intensities themselves (i.e., no “feature extraction” is taking place).

The end result is a facial landmark detector that can be used to detect facial landmarks in real-time with high quality predictions.

For more information and details on this specific technique, be sure to read the paper by Kazemi and Sullivan linked to above, along with the official dlib announcement.

Understanding dlib’s facial landmark detector

The pre-trained facial landmark detector inside the dlib library is used to estimate the location of 68 (x, y)-coordinates that map to facial structures on the face.

The indexes of the 68 coordinates can be visualized on the image below:

Figure 2: Visualizing the 68 facial landmark coordinates from the iBUG 300-W dataset (higher resolution).

These annotations are part of the 68 point iBUG 300-W dataset which the dlib facial landmark predictor was trained on.

It’s important to note that other flavors of facial landmark detectors exist, including the 194 point model that can be trained on the HELEN dataset.

Regardless of which dataset is used, the same dlib framework can be leveraged to train a shape predictor on the input training data — this is useful if you would like to train facial landmark detectors or custom shape predictors of your own.

In the remaining of this blog post I’ll demonstrate how to detect these facial landmarks in images.

Future blog posts in this series will use these facial landmarks to extract specific regions of the face, apply face alignment, and even build a blink detection system.

Detecting facial landmarks with dlib, OpenCV, and Python

In order to prepare for this series of blog posts on facial landmarks, I’ve added a few convenience functions to my imutils library, specifically inside face_utils.py.

We’ll be reviewing two of these functions inside

face_utils.py

  now and the remaining ones next week.

The first utility function is

rect_to_bb

 , short for “rectangle to bounding box”:

# import the necessary packages
from collections import OrderedDict
import numpy as np
import cv2

# define a dictionary that maps the indexes of the facial
# landmarks to specific face regions
FACIAL_LANDMARKS_IDXS = OrderedDict([
        ("mouth", (48, 68)),
        ("right_eyebrow", (17, 22)),
        ("left_eyebrow", (22, 27)),
        ("right_eye", (36, 42)),
        ("left_eye", (42, 48)),
        ("nose", (27, 35)),
        ("jaw", (0, 17))
])

def rect_to_bb(rect):
        # take a bounding predicted by dlib and convert it
        # to the format (x, y, w, h) as we would normally do
        # with OpenCV
        x = rect.left()
        y = rect.top()
        w = rect.right() - x
        h = rect.bottom() - y

        # return a tuple of (x, y, w, h)
        return (x, y, w, h)

This function accepts a single argument,

rect

 , which is assumed to be a bounding box rectangle produced by a dlib detector (i.e., the face detector).

The

rect

  object includes the (x, y)-coordinates of the detection.

However, in OpenCV, we normally think of a bounding box in terms of “(x, y, width, height)” so as a matter of convenience, the

rect_to_bb

  function takes this

rect

  object and transforms it into a 4-tuple of coordinates.

Again, this is simply a matter of conveinence and taste.

Secondly, we have the

shape_to_np

  function:

# import the necessary packages
from collections import OrderedDict
import numpy as np
import cv2

# define a dictionary that maps the indexes of the facial
# landmarks to specific face regions
FACIAL_LANDMARKS_IDXS = OrderedDict([
        ("mouth", (48, 68)),
        ("right_eyebrow", (17, 22)),
        ("left_eyebrow", (22, 27)),
        ("right_eye", (36, 42)),
        ("left_eye", (42, 48)),
        ("nose", (27, 35)),
        ("jaw", (0, 17))
])

def rect_to_bb(rect):
        # take a bounding predicted by dlib and convert it
        # to the format (x, y, w, h) as we would normally do
        # with OpenCV
        x = rect.left()
        y = rect.top()
        w = rect.right() - x
        h = rect.bottom() - y

        # return a tuple of (x, y, w, h)
        return (x, y, w, h)

def shape_to_np(shape, dtype="int"):
        # initialize the list of (x, y)-coordinates
        coords = np.zeros((68, 2), dtype=dtype)

        # loop over the 68 facial landmarks and convert them
        # to a 2-tuple of (x, y)-coordinates
        for i in range(0, 68):
                coords[i] = (shape.part(i).x, shape.part(i).y)

        # return the list of (x, y)-coordinates
        return coords

The dlib face landmark detector will return a

shape

  object containing the 68 (x, y)-coordinates of the facial landmark regions.

Using the

shape_to_np

  function, we cam convert this object to a NumPy array, allowing it to “play nicer” with our Python code.

Given these two helper functions, we are now ready to detect facial landmarks in images.

Open up a new file, name it

facial_landmarks.py

 , and insert the following code:

# import the necessary packages
from imutils import face_utils
import numpy as np
import argparse
import imutils
import dlib
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
        help="path to facial landmark predictor")
ap.add_argument("-i", "--image", required=True,
        help="path to input image")
args = vars(ap.parse_args())

Lines 2-7 import our required Python packages.

We’ll be using the

face_utils

  submodule of

imutils

  to access our helper functions detailed above.

We’ll then import

dlib

 . If you don’t already have dlib installed on your system, please follow the instructions in my previous blog post to get your system properly configured.

Lines 10-15 parse our command line arguments:

• --shape-predictor
  

   : This is the path to dlib’s pre-trained facial landmark detector. You can download the detector model here or you can use the “Downloads” section of this post to grab the code + example images + pre-trained detector as well.

• --image
  

   : The path to the input image that we want to detect facial landmarks on.

Now that our imports and command line arguments are taken care of, let’s initialize dlib’s face detector and facial landmark predictor:

# import the necessary packages
from imutils import face_utils
import numpy as np
import argparse
import imutils
import dlib
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
        help="path to facial landmark predictor")
ap.add_argument("-i", "--image", required=True,
        help="path to input image")
args = vars(ap.parse_args())

# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

Line 19 initializes dlib’s pre-trained face detector based on a modification to the standard Histogram of Oriented Gradients + Linear SVM method for object detection.

Line 20 then loads the facial landmark predictor using the path to the supplied

--shape-predictor

 .

But before we can actually detect facial landmarks, we first need to detect the face in our input image:

# import the necessary packages
from imutils import face_utils
import numpy as np
import argparse
import imutils
import dlib
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
        help="path to facial landmark predictor")
ap.add_argument("-i", "--image", required=True,
        help="path to input image")
args = vars(ap.parse_args())

# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

# load the input image, resize it, and convert it to grayscale
image = cv2.imread(args["image"])
image = imutils.resize(image, width=500)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# detect faces in the grayscale image
rects = detector(gray, 1)

Line 23 loads our input image from disk via OpenCV, then pre-processes the image by resizing to have a width of 500 pixels and converting it to grayscale (Lines 24 and 25).

Line 28 handles detecting the bounding box of faces in our image.

The first parameter to the

detector

  is our grayscale image (although this method can work with color images as well).

The second parameter is the number of image pyramid layers to apply when upscaling the image prior to applying the detector (this it the equivalent of computing cv2.pyrUp N number of times on the image).

The benefit of increasing the resolution of the input image prior to face detection is that it may allow us to detect more faces in the image — the downside is that the larger the input image, the more computaitonally expensive the detection process is.

Given the (x, y)-coordinates of the faces in the image, we can now apply facial landmark detection to each of the face regions:

# import the necessary packages
from imutils import face_utils
import numpy as np
import argparse
import imutils
import dlib
import cv2

# construct the argument parser and parse the arguments
ap = argparse.ArgumentParser()
ap.add_argument("-p", "--shape-predictor", required=True,
        help="path to facial landmark predictor")
ap.add_argument("-i", "--image", required=True,
        help="path to input image")
args = vars(ap.parse_args())

# initialize dlib's face detector (HOG-based) and then create
# the facial landmark predictor
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(args["shape_predictor"])

# load the input image, resize it, and convert it to grayscale
image = cv2.imread(args["image"])
image = imutils.resize(image, width=500)
gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY)

# detect faces in the grayscale image
rects = detector(gray, 1)

# loop over the face detections
for (i, rect) in enumerate(rects):
        # determine the facial landmarks for the face region, then
        # convert the facial landmark (x, y)-coordinates to a NumPy
        # array
        shape = predictor(gray, rect)
        shape = face_utils.shape_to_np(shape)

        # convert dlib's rectangle to a OpenCV-style bounding box
        # [i.e., (x, y, w, h)], then draw the face bounding box
        (x, y, w, h) = face_utils.rect_to_bb(rect)
        cv2.rectangle(image, (x, y), (x + w, y + h), (0, 255, 0), 2)

        # show the face number
        cv2.putText(image, "Face #{}".format(i + 1), (x - 10, y - 10),
                cv2.FONT_HERSHEY_SIMPLEX, 0.5, (0, 255, 0), 2)

        # loop over the (x, y)-coordinates for the facial landmarks
        # and draw them on the image
        for (x, y) in shape:
                cv2.circle(image, (x, y), 1, (0, 0, 255), -1)

# show the output image with the face detections + facial landmarks
cv2.imshow("Output", image)
cv2.waitKey(0)

We start looping over each of the face detections on Line 31.

For each of the face detections, we apply facial landmark detection on Line 35, giving us the 68 (x, y)-coordinates that map to the specific facial features in the image.

Line 36 then converts the dlib

shape

  object to a NumPy array with shape (68, 2).

Lines 40 and 41 draw the bounding box surrounding the detected face on the

image

  while Lines 44 and 45 draw the index of the face.

Finally, Lines 49 and 50 loop over the detected facial landmarks and draw each of them individually.

Lines 53 and 54 simply display the output

image

  to our screen.

Facial landmark visualizations

Before we test our facial landmark detector, make sure you have upgraded to the latest version of

imutils

  which includes the

face_utils.py

  file:

$ pip install --upgrade imutils

Note: If you are using Python virtual environments, make sure you upgrade the

imutils

  inside the virtual environment.

From there, use the “Downloads” section of this guide to download the source code, example images, and pre-trained dlib facial landmark detector.

Once you’ve downloaded the .zip archive, unzip it, change directory to

facial-landmarks

 , and execute the following command:

$ python facial_landmarks.py --shape-predictor shape_predictor_68_face_landmarks.dat \
        --image images/example_01.jpg

Figure 3: Applying facial landmark detection using dlib, OpenCV, and Python.

Notice how the bounding box of my face is drawn in green while each of the individual facial landmarks are drawn in red.

The same is true for this second example image:

$ python facial_landmarks.py --shape-predictor shape_predictor_68_face_landmarks.dat \
        --image images/example_02.jpg

Figure 4: Facial landmarks with dlib.

Here we can clearly see that the red circles map to specific facial features, including my jawline, mouth, nose, eyes, and eyebrows.

Let’s take a look at one final example, this time with multiple people in the image:

$ python facial_landmarks.py --shape-predictor shape_predictor_68_face_landmarks.dat \
        --image images/example_03.jpg

Figure 5: Detecting facial landmarks for multiple people in an image.

For both people in the image (myself and Trisha, my fiancée), our faces are not only detected but also annotated via facial landmarks as well.

Summary

In today’s blog post we learned what facial landmarks are and how to detect them using dlib, OpenCV, and Python.

Detecting facial landmarks in an image is a two step process:

1. First we must localize a face(s) in an image. This can be accomplished using a number of different techniques, but normally involve either Haar cascades or HOG + Linear SVM detectors (but any approach that produces a bounding box around the face will suffice).
2. Apply the shape predictor, specifically a facial landmark detector, to obtain the (x, y)-coordinates of the face regions in the face ROI.

Given these facial landmarks we can apply a number of computer vision techniques, including:

• Face part extraction (i.e., nose, eyes, mouth, jawline, etc.)
• Facial alignment
• Head pose estimation
• Face swapping
• Blink detection
• …and much more!

In next week’s blog post I’ll be demonstrating how to access each of the face parts individually and extract the eyes, eyebrows, nose, mouth, and jawline features simply by using a bit of NumPy array slicing magic.

To be notified when this next blog post goes live, be sure to enter your email address in the form below!

Downloads:

If you would like to download the code and images used in this post, please enter your email address in the form below. Not only will you get a .zip of the code, I’ll also send you a FREE 11-page Resource Guide on Computer Vision and Image Search Engines, including exclusive techniques that I don’t post on this blog! Sound good? If so, enter your email address and I’ll send you the code immediately!

Email address:

The post Facial landmarks with dlib, OpenCV, and Python appeared first on PyImageSearch.

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U.S. Crew Half Duty Day: Following yesterday’s successful EVA, today was a half duty day for the US crew. They executed standard post EVA activities including a Extravehicular Mobility Unit (EMU) water recharge, returning equipment to the Airlock, Metal Oxide (METOX) regeneration, battery maintenance, and a debrief with ground teams.  Habitability Observations: The crew documented and submitted observations per tasks from the last few weeks related to human factors and habitability. The crew selects from various topics including housekeeping activities, trash management, accumulation of dust, items not stowed, frequency of housekeeping, and effectiveness of housekeeping tools. The investigation collects observations about the relationship between crewmembers and their environment on the ISS. Observations can help spacecraft designers understand how much habitable volume is required, and whether a mission’s duration impacts how much space crew members need. Space Headaches Questionnaire: The crew performed their weekly questionnaire, answering questions utilizing the Data Collection Tool. The European Space Agency (ESA) investigation collects information that may help in the development of methods to alleviate associated symptoms and improvement in the well-being and performance of crewmembers in space. Headaches during space flight can negatively affect mental and physical capacities of crewmembers that can influence performance during a space mission. Today’s Planned Activities All activities were completed unless otherwise noted. KORREKTSIYA. Logging Liquid and Food (Medicine) Intake Soyuz 732 Descent Drill and Return Equipment List & Stowage Consultation HMS Periodic Health Status (PHS) Post EVA Examination Cygnus PROX Switch OFF Water Recovery System Waste Water Tank Drain Termination Strata Status Check ISS Crew departure preparation LBNP Training (PRELIMINARY) JEM System Laptop Terminal Reboot Inspect CWC-I attached to UPA SPA. Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill Combustion Integrated Rack Alignment Guide Removal Sokol Space Suit leak check Replacement СПП-2 in [АСУ] Multi-purpose Small Payload Rack (MSPR) /Group Combustion Module (GCM) Component Deactivation Sokol Suit Dryout, Setup Suits 1 and 2 for Drying Robotic Workstation (RWS) Teardown LBNP Training Extravehicular Activity (EVA) Debrief On MCC GO MPEG2 Multicast and Unicast Video Streaming Test PROBIOVIT. Setup of Probiovit Kits No.3, No.4 in ТБУ-В at +4 °С KORREKTSIYA. Logging Liquid and Food (Medicine) Intake Hardware prepack for return and disposal on Soyuz 732 Terminate Suits 1, 2 Dryout Extravehicular Mobility Unit (EMU) Water Recharge ISS HAM Radio and Video Power Up Meteor Shutter Open Start drying the 3rd space suit and setup the 1st pair of gloves for drying Photo/TV Extravehicular Activity (EVA) Camera Disassembly Removal of [АСН-К] Navigation Module from Progress 435.Tagup with specialists as necessary PROBIOVIT. Cryogem-03 Removal EVA Airlock Restow Regenerative Environmental Control and Life Support System (RGN) Wastewater Storage Tank Assembly (WSTA) Fill Finish drying the 1st pair of gloves and start drying the 2nd pair Metal Oxide (METOX) Regeneration Termination Habitability Human Factors Directed Observations Long Duration Sorbent Testbed Status Check. Actiwatch Spectrum HRF1 Configuration Alternate 1 Terminate drying the second pair of gloves Pille Dosimeter Readout after US EVA Pre-pack cargo items for return or disposal on Soyuz 732 Space Headaches – Weekly Questionnaire Nikon still camera sync with station time Finish drying the 3rd suit, start drying the 3rd pair of gloves                  Completed Task List Items None  Ground Activities All activities were completed unless otherwise noted. Post EVA support Incorporate EXT R9 patch on all connected PCSs Three-Day Look Ahead: Saturday, 04/01: Crew off duty, housekeeping Sunday, 04/02: Crew off duty Monday, 04/03: PEPS inspection, Story Time From Space, ER7 locker install QUICK ISS Status – Environmental Control Group:   Component Status Elektron On Vozdukh Manual [СКВ] 1 – SM Air Conditioner System (“SKV1”) Off           [СКВ] 2 – SM Air Conditioner System (“SKV2”) On Carbon Dioxide Removal Assembly (CDRA) Lab Standby Carbon Dioxide Removal Assembly (CDRA) Node 3 Operate Major Constituent Analyzer (MCA) Lab Operate Major Constituent Analyzer (MCA) Node 3 Standby Oxygen Generation Assembly (OGA) Process Urine Processing Assembly (UPA) Reprocess Trace Contaminant Control System (TCCS) Lab Off Trace Contaminant Control System (TCCS) Node 3 Full Up

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I have a new follower on Twitter

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Near the outskirts of the Small Magellanic Cloud, a satellite galaxy some 200 thousand light-years distant, lies 5 million year young star cluster NGC 602. Surrounded by natal gas and dust, NGC 602 is featured in this stunning Hubble image of the region, augmented by images in the X-ray by Chandra, and in the infrared by Spitzer. Fantastic ridges and swept back shapes strongly suggest that energetic radiation and shock waves from NGC 602's massive young stars have eroded the dusty material and triggered a progression of star formation moving away from the cluster's center. At the estimated distance of the Small Magellanic Cloud, the Picture spans about 200 light-years, but a tantalizing assortment of background galaxies are also visible in this sharp multi-colored view. The background galaxies are hundreds of millions of light-years or more beyond NGC 602. via NASA http://ift.tt/2oKD0Ws