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# Deep Learning Image Compression: nearly 10,000:1 compression ratio!

Tuesday, June 28, 2022

Here disclosed is a novel compression technique I call Deep Learning Semantic Vector Quantization (DLSVC) that achieves in this sample 9,039:1 compression! Compare this to JPEG at about 10:1 or even HEIC at about 20:1, and the absolutely incredible power of DL image compression becomes apparent.

Before I disclose the technique to achieve this absolutely stunning result, we need to understand a bit about the psychovisual mechanisms that are being exploited. A good starting point is thinking about:

It was a dark and stormy night and all through the house not a creature was stirring, not even a mouse.

I’m sure each person reading this develops an internal model, likely some combination of a snug, warm indoor Christmas scene while outside a storm raged, or something to that effect derived from the shared cultural semantic representation: a scene with a great deal of detail and complexity, despite the very short text string. The underlying mechanism is a sort of vector quantization where the text represents a series of vectors that semantically reference complex culturally shared elements that form a type of codebook.

If a person skilled at drawing were to attempt to represent this coded reference visually, it is likely the result would be recognizable to others as a representation of the text; that is, the text is an extremely compact symbolic representation of an image.

So now lets try a little AI assisted vector quantization of images.  We can start with the a generic image from Wikipedia:

Next we use AI to reduce the image to a symbolic semantic representation.  There are far more powerful AI systems available, but we’ll use one that allows normal people to play with it, @milhidaka’s caption generator on github:

This is a cat sitting on top of a wooden bench which we can LZW compress assuming 26 character text to a mere 174 bits or 804D22134C834638D4CE3CE14058E38310D071087. That’s a pretty compact representation of an image!  The model has been trained to understand a correlation between widely shared semantic symbols and elements of images and can reduce an image to a human-comprehensible, compact textual representation, effectively a lossy coding scheme referencing a massive shared codebook with complex grammatical rules that further increase the information density of the text.

Decoding those 174 bits back to the original text, we can feed them into an image generating generative AI model, like DALL·E mini and we get our original image back by reversing the process leveraging a different semantic model, but one also trained to the same human language.

It is clearly a lossy conversion, but here’s the thing: so too is human memory lossy.  If you saw the original scene and 20 years later, someone said, “hey, remember that time we saw the cat sitting on a wooden bench in Varna, look, here’s a picture of it!” and showed you this picture, I mean aside from the funny looking cat like blob, you’d say “oh, yeah, cool, that was a cute cat.”

Using the DALL·E mini output as the basis for computing compression rather than the input image which could be arbitrarily large, we have 256×256×8×3 bits output = 1,572,864 bits to represent the output image raw.

WebP “low quality” compressing the 256×256 image yields a file of 146,080 bits or 10.77:1 compression.

My technique yields a compressed representation of 174 bits or 9,039:1 compression. DALL·E 2‘s 1024×1024 output size should yield in 144,624:1 compression.

Pied Piper got nothin’ on this!

Posted at 11:51:14 GMT-0700

Category: HowToLinuxphototechnology

# Compile and install Digikam on Ubuntu 20.04 Focal (21.10 too)

Friday, March 26, 2021

Digikam is an incredibly powerful media management tool that integrates a great collection of powerful media processing projects into a single, fairly nice and moderately intuitive user interface. The problem is that it make use of SO many projects and libraries that installation is quite fragile and most distributions are many years out of date – that is a typical sudo apt install digikam will yield version 4.5 while release is (as of this writing) 7.5.

In particular, this newer version has face detection that runs LOCALLY – not on Google or Facebook’s servers – meaning you don’t have to trade your personal photos and all the data implicit in them to a data broker to make use of such a useful tool.  Sure, Google once bought and then improved Picasa Desktop which gave you this function, but then they realized this was cutting into their data harvesting business and discontinued Picasa and tried to convince people to let them look at all their pictures with Google Photos.  We really, really need to make personal data a toxic asset, such an intolerable liability that any company that holds any personal data has negative value.  But until then, use FOSS software on your own hardware where ever possible.

You can compile the latest version on Ubuntu 20.04 Focal Fossa, though not exactly painlessly, or you can install the flatpak easily. I hate flatpaks with a passion, so I went through the exercise and found what appears to be stable success with the following procedure which yielded a fully featured digikam with zero dependency errors or warnings and all features enabled using MariaDB as a backend.

Updating Ubuntu from 20.04 to 21.10 (probably any other major update too) will (as typical) break a ton of stuff.  For “reasons” the updater uninstalls all sorts of things like MariaDB and many of the dependencies.  Generally, as libraries change versions, recompiling is required.  This is so easy with FreeBSD ports…

sudo apt update
sudo mysql_secure_installation

The secure options are all good, accept them unless you know better.

Start the server (if it isn’t)

sudo systemctl start mariadb.service


Do some really basic config:

sudo nano /etc/mysql/mariadb.conf.d/50-server.cnf


and set:

character-set-server = utf8mb4
collation-server = utf8mb4_general_ci
default_storage_engine = InnoDB


Switch to mariadb and create an admin user account and (I’d suggest) one for digikam.  It seems this has to be done before the first connect and can’t be fixed after.  You’ll probably want to use a different ‘user’ than I did, but feel free.

sudo mariadb
CREATE USER 'gessel'@'localhost' IDENTIFIED BY 'password';
GRANT ALL ON *.* TO 'gessel'@'localhost' IDENTIFIED BY 'password';
CREATE DATABASE digikam;
GRANT ALL PRIVILEGES ON digikam.* TO 'gessel'@'localhost';
FLUSH PRIVILEGES;


should correctly create the correct user – though check the instructions tab on the database connection options pane for any changes if you’re following these instructions for install of a later version. You will need the socket location to connect to the database so before exit; run:

mysqladmin -u admin -p version


Should yield something like:

Enter password:

Protocol version	10
Connection		Localhost via UNIX socket
UNIX socket		/var/run/mysqld/mysqld.sock
Uptime:			5 hours 26 min 6 sec

Threads: 29  Questions: 6322899  Slow queries: 0  Opens: 108  Flush tables: 1  Open tables: 74  Queries per second avg: 323.157


And note the value for UNIX socket, you’re going to need that later: /var/run/mysqld/mysqld.sock – yours might vary.

### Install digiKam Dependencies

• Updated to libx264-163 and libx265-199
• Version change from 7.2.0 to 7.3.0

• Installing on Ubuntu 21.10 “impish”
• Version change to 7.5.0 (note camelcase used for file name now, “digiKam” not “digikam“)
• Problem with libopencv-dev required selecting a # sudo aptitude install solution to get past a libilmbase-dev but it is not installable error.

Digikam has just a few dependencies.just a few... the below command should install the needed for 7.30 on Ubuntu 21.10. Any other version combination might be different.:

sudo aptitude install \
bison \
checkinstall \
devscripts \
doxygen \
extra-cmake-modules \
ffmpeg \
ffmpegthumbnailer \
flex \
graphviz \
help2man \
jasper \
libavcodec-dev \
libavdevice-dev \
libavfilter-dev \
libavformat-dev \
libavutil-dev \
libboost-dev \
libboost-graph-dev \
libeigen3-dev \
libexiv2-dev \
libgphoto2-dev \
libjasper-dev \
libjasper-runtime \
libjasper4 \
libjpeg-dev \
libkf5calendarcore-dev \
libkf5contacts-dev \
libkf5doctools-dev \
libkf5kipi-dev \
libkf5notifyconfig-dev \
libkf5sane-dev \
libkf5solid-dev \
libkf5xmlgui-dev \
liblcms2-dev \
liblensfun-dev \
liblqr-1-0-dev \
libmagick++-6.q16-dev \
libmagick++-6.q16hdri-dev \
libmagickcore-dev \
libmarble-dev \
libqt5opengl5-dev \
libqt5sql5-mysql \
libqt5svg5-dev \
libqt5webkit5-dev \
libqt5webview5 \
libqt5webview5-dev \
libqt5x11extras5-dev \
libqt5xmlpatterns5-dev \
libqtav-dev \
libqtwebkit-dev \
libswscale-dev \
libtiff-dev \
libusb-1.0-0-dev \
libx264-163 \
libx264-dev \
libx265-199 \
libx265-dev \
libxml2-dev \
libxslt1-dev \
marble \
pkg-kde-tools \
qtbase5-dev \
qtbase5-dev-tools \
qtmultimedia5-dev \
qtwebengine5-dev \
libopencv-dev \
qtwebengine5-dev-tools


### Compile Digikam

Switch to your projects directory (~/projects, say) and get the source, cross your fingers, and go to town. The make -j4 command will take a while to compile everything.  There are two basic mechanisms for getting the source code: wget the taball or git pull the repository.

wget https://download.kde.org/stable/digikam/7.5.0/digiKam-7.5.0.tar.xz
tar -xvf digiKam-7.5.0.tar.xz
cd digiKam-7.5.0.tar.xz


#### git pull the repository

Git uses branches/tags so check the pull down list of latest branches and tags at the top left, below the many, many branches is the tag list at https://invent.kde.org/graphics/digikam/-/tree/v7.5.0 , latest on top, and currently 7.5.0. This is currently a 1.4 GB git pull (!!).
There was an issue in the v7.3.0 tag that caused built to fail that was fixed in current, so building “stable” isn’t always the best choice for stability.

git clone -b v7.5.0 https://invent.kde.org/graphics/digikam.git
cd digikam


./bootstrap.linux
cd build
make -j4
sudo su
make install/fast


Compiling might take 15-30 minutes depending on CPU.  Adjust -jx to optimize build times, the normal rule of thumb is that x=# of cores or cores+1, YMMV, 4 is a reasonable number if you aren’t confident or interested in experimenting.

The ./bootstrap.linux result should be as below; if it indicates a something is missing then double check dependencies.  If you’ve never compiled anything before, you might need to install cmake and and some other basics not in the apt install list above:

-- ----------------------------------------------------------------------------------
--  digiKam 7.2.0 dependencies results   <https://www.digikam.org>
--
--  MySQL Database Support will be compiled.. YES (optional)
--  MySQL Internal Support will be compiled.. YES (optional)
--  DBUS Support will be compiled............ YES (optional)
--  App. Style Support will be compiled...... YES (optional)
--  QWebEngine Support will be compiled...... YES (optional)
--  libboostgraph found...................... YES
--  libexiv2 found........................... YES
--  libexpat found........................... YES
--  libjpeg found............................ YES
--  libkde found............................. YES
--  liblcms found............................ YES
--  libopencv found.......................... YES
--  libpng found............................. YES
--  libqt found.............................. YES
--  libtiff found............................ YES
--  bison found.............................. YES (optional)
--  doxygen found............................ YES (optional)
--  ccache found............................. YES (optional)
--  flex found............................... YES (optional)
--  libmagick++ found........................ YES (optional)
--  libeigen3 found.......................... YES (optional)
--  libgphoto2 found......................... YES (optional)
--  libjasper found.......................... YES (optional)
--  libkcalendarcore found................... YES (optional)
--  libkiconthemes found..................... YES (optional)
--  libkio found............................. YES (optional)
--  libknotifyconfig found................... YES (optional)
--  libksane found........................... YES (optional)
--  liblensfun found......................... YES (optional)
--  liblqr-1 found........................... YES (optional)
--  libmarble found.......................... YES (optional)
--  libqtav found............................ YES (optional)
--  libxml2 found............................ YES (optional)
--  libxslt found............................ YES (optional)
--  libx265 found............................ YES (optional)
--  OpenGL found............................. YES (optional)
--  libqtxmlpatterns found................... YES (optional)
--  digiKam can be compiled.................. YES
-- ----------------------------------------------------------------------------------


### Launch and configure Digikam

(if you’re still root, exit root before launching # digikam)

The Configuration options are pretty basic, but note that to configure the Digikam back end you’ll need to use that MariaDB socket value you got before and the user you created like so UNIX_SOCKET=/var/run/mysqld/mysqld.sock:

On the first run, it will download about 350mb of code for the face recognition engine.  Hey – maybe a bit heavy, but you’re not giving the Google or Apple free lookie looks at all your personal pictures.  Also, if all this is a bit much (and, Frankly, it is) I’d consider Digikam one of the few applications that makes the whole flatpak thing seem somewhat justified.  Maybe.

I recommend mysqltuner highly, then maybe check this out (or just leave it default, default works well).

Tuning a database is application and computer specific, there’s no one size fits any, certainly not all, and it may change as your database grows. There are far more expert and complete tuning guides available, but here’s what I do:

#### Pre-Tuning Data Collection

Tuning at the most basic involves instrumenting the database to log problems, running it for a while, then parsing the performance logs for useful hints. The mysqltuner.pl script is far more expert at than I’ll ever be, so I pretty much just trust it. You have to modify your mysqld.cnf file to enable performance data collection (which, BTW, slows down operation, so undo this later) which, for MariaDB, means adding a few lines:

sudo nano /etc/mysql/mariadb.conf.d/50-server.cnf
# enable performance schema to allow optimization, but ironically hit performance, so disable after tuning.
# in the [mysqld] section insert
performance_schema=ON
performance-schema-instrument='stage/%=ON'
performance-schema-consumer-events-stages-current=ON
performance-schema-consumer-events-stages-history=ON
performance-schema-consumer-events-stages-history-long=ON


I rather like this guide’s helpful instructions for putting the script in /usr/local/sbin/ so it is in the execution path:

sudo wget https://raw.githubusercontent.com/major/MySQLTuner-perl/master/mysqltuner.pl -O /usr/local/sbin/mysqltuner.pl
sudo chmod 700 /usr/local/sbin/mysqltuner.pl
sudo mysqltuner.pl


Then restart with sudo service mariadb restart then go about your business with digikam – make sure you rack up some real hours to gather useful data on your performance. Things like ingesting a large collection should generate useful data. I’d suggest doing disk tuning first because that’s hardware not load dependent.

#### Disk tuning

Databases tend to hammer storage and SSDs, especially SLC/enterprise SSDs, massively improve DB performance over spinning disks – unless you have a massive array of really good rotating drives. I’m running this DB on one spinning disk, so performance is very MEH. MySQL and MariaDB make some assumptions about disk performance which is used to scale some pretty important parameters for write caching. You can meaningfully improve on the defaults by testing your disk with a great linux utility called “fio”.

sudo apt install fio
fio --randrepeat=1 --ioengine=libaio --direct=1 --gtod_reduce=1 --name=test --filename=test --bs=4k --iodepth=64 --size=4G --readwrite=randrw --rwmixread=75


This will take a while and will give some very detailed information about the performance of your disk subsystem, the key parameters being average and max write IOPS. I typically create a # performance tuning section at the end of my [mysqld] section and before [embedded] and I’ll put these values in as, say: (your IOPS values will be different):

# performance tuning

innodb_io_capacity              = 170
innodb_io_capacity_max          = 286


and sudo service mariadb restart

#### Using mysqltuner.pl

After you’ve collected some data, there may be a list of tuning options.

sudo nano /etc/mysql/mariadb.conf.d/50-server.cnf

Mine currently look like this, but they’ll change as the database stabilizes and my usage patterns change.

# performance tuning

innodb_io_capacity              = 170
innodb_io_capacity_max          = 286

innodb_buffer_pool_size         = 4G
innodb_log_file_size            = 512M
innodb_buffer_pool_instances    = 4
skip_name_resolve               = 1
query_cache_size                = 0
query_cache_type                = 0
query_cache_limit               = 2M
max_connections                 = 175
join_buffer_size                = 4M
tmp_table_size                  = 24M
max_heap_table_size             = 24M
innodb_buffer_pool_size         = 4G
max_allowed_packet              = 128M


and

sudo service mariadb restart

Note max_allowed_packet = 128M comes from this guide. I trust it, but it isn’t a mysqltuner suggestion.

Posted at 17:11:21 GMT-0700

Category: HowToLinuxphotoPositivereviewstechnology

# WebP and SVG

Tuesday, September 1, 2020

Using WebP coded images inside SVG containers works.  I haven’t found any automatic way to do it, but it is easy enough manually and results in very efficiently coded images that work well on the internets.  The manual process is to Base64 encode the WebP image and then open the .svg file in a text editor and replace the

xlink:href="data:image/png;base64, ..."

with

xlink:href="data:image/webp;base64,..."

(“…” means the appropriate data, obviously).

Back in about 2010 Google released the spec for WebP, an image compression format that provides a roughly 2-4x coding efficiency over the venerable JPEG (vintage 1974), derived from the VP8 CODEC they bought from ON2. VP8 is a contemporary of and technical equivalent to H.264 and was developed during a rush of innovation to replace the aging MPEG-II standard that included Theora and Dirac. Both VP8 and H.264 CODECs are encumbered by patents, but Google granted an irrevocable license to all patents, making it “open,” while H.264s patents compel licensing from MPEG-LA.  One would think this would tend to make VP8 (and the WEBM container) a global standard, but Apple refused to give Google the win and there’s still no native support in Apple products.

A small aside on video and still coding techniques.

All modern “lossy” (throwing some data away like .mp3, as opposed to “lossless” meaning the original can be reconstructed exactly, as in .flac) CODECs are founded on either Discrete Cosine Transform (DCT) or Wavelet (DWT) encoding of “blocks” of image data.  There are far more detailed write ups online that explain the process in detail, but the basic concept is to divide an image into small tiles of data then apply a mathematical function that converts that data into a form which sorts the information from least human-perceptible to most human-perceptible and sets some threshold for throwing away the least important data while leaving the bits that are most important to human perception.

Wavelets are promising, but never really took off, as in JPEG2000 and Dirac (which was developed by the BBC).  It is a fairly safe bet that any video or still image you see is DCT coded thanks to Nasir Ahmed, T. Natarajan and K. R. Rao.  The differences between 1993’s MPEG-1 and 2013’s H.265 are largely around how the data that is perceptually important is encoded in each still (intra-frame coding) and some very important innovations in inter-frame coding that aren’t relevant to still images.

It is the application of these clever intra-frame perceptual data compression techniques that is most relevant to the coding efficiency difference between JPEG and WebP.

Back to the good stuff…

Way back in 2010 Google experimented with the VP8 intra-coding techniques to develop WebP, a still image CODEC that had to have two core features:

• better coding efficiency than JPEG,
• ability to handle transparency like .png or .tiff.

This could be the one standard image coding technique to rule them all – from icons to gigapixel images, all the necessary features and many times better coding efficiency than the rest.  Who wouldn’t love that?

Apple.

Of course it was Apple.  Can’t let Google have the win.  But, finally, with Safari 14 (June 22, 2020 – a decade late!) iOS users can finally see WebP images and websites don’t need crazy auto-detect 1974 tech substitution tricks.  Good job Apple!

It may not be a coincidence that Apple has just released their own still image format based on the intra-frame coding magic of H.265, .heif and maybe they thought it might be a good idea to suddenly pretend to be an open player rather than a walled-garden-screw-you lest iOS insta-users wall themselves off from the 90% of the world that isn’t willing to pay double to pose with a fashionable icon in their hands.  Not surprisingly, .heic, based on H.265 developments is meaningfully more efficient than WebP based on VP8/H.264 era techniques, but as it took WebP 10 years to become a usable web standard, I wouldn’t count on .heic  having universal support soon.

Oh well.  In the mean time, VP8 gave way to VP9 then to VP10, which has now AV1, arguably a generation ahead of HEVC/H.265.  There’s no hardware decode (yet, as of end of 2020) but all the big players are behind it, so I expect 2021 devices will and GPU decode will come in 2021. By then, expect VVC (H.266) to be replacing HEVC (H.265) with a ~35% coding efficiency improvement.

Along with AV1’s intra/inter-frame coding advance, the intra-frame techniques are useful for a still format called AVIF, basically AVIF is to AV1 (“VP11”) what WEBP is to VP8 and HEIF is to HEVC. So far (Dec 2020) only Chrome and Opera support AVIF images.

Then, of course, there’s JPEG XL on the way.  For now, the most broadly supported post-JPEG image codec is WEBP.

SVG support in browsers is a much older thing – Apple embraced it early (SVG was not developed by Google so….) and basically everything but IE has full support (IE…  the tool you use to download a real browser).  So if we have SVG and WebP, why not both together?

Oddly I can’t find support for this in any of the tools I use, but as noted at the open, it is pretty easy.  The workflow I use is to:

• generate a graphic in GIMP or Photoshop or whatever and save as .png or .jpg as appropriate to the image content with little compression (high image quality)
• Combine that with graphics in Inkscape.
• If the graphics include type, convert the type to SVG paths to avoid font availability problems or having to download a font file before rendering the text or having it render randomly.
• Save the file (as .svg, the native format of Inkscape)
• Convert the image file to WebP with a reasonable tool like Nomacs or Ifranview.
• Base64 encode the image file, either with base64 # base64 infile.webp > outfile.webp.b64 or with this convenient site
• If you use the command line option the prefix to the data is “data:image/webp;base64,
• Replace the … on the appropriate xlink:href="...." with the new data using a text editor like Atom.
• Drop the file on a browser page to see if it works.

WordPress blocks .svg uploads without a plugin, so you need one

The picture is 101.9kB and tolerates zoom quite well. (give it a try, click and zoom on the image).

Posted at 08:54:16 GMT-0700

Category: HowToLinuxphotoself-publishingtechnology

# Dealing with Apple Branded HEIF .HEIC files on Linux

Saturday, August 22, 2020

Some of the coding tricks in H.265 have been incorporated into MPEG-H coding, an ISO standard introduced in 2017, which yields a roughly 2:1 coding efficiency gain over the venerable JPEG, which was introduced in 1992.  Remember that?  I do; I’m old.  I remember having a hardware NUBUS JPEG decoder card.   One of the reasons JPEG has lasted so long is that images have become a small storage burden (compared to 4k video, say) and that changing format standards is extremely annoying to everyone.

Apple has elected to make every rational person’s life difficult and put a little barbed wire around their high-fashion walled garden and do something a little special with their brand of a HEVC (h.265) profile for images.  Now normally seeing iOS user’s insta images of how fashionable they are isn’t really worth the effort, but now and then a useful correspondent joins the cult and forks over a ton of money to show off a logo and starts sending you stuff in their special proprietary format.  Annoying, but fixable.

Assuming you’re using an OS that is neither primarily spyware nor fashion forward, such as Linux Mint, you can install HEIF decode (including Apple Brand HEIC) with a few simple commands:

$sudo add-apt-repository ppa:jakar/qt-heif$ sudo apt update
\$ sudo apt install qt-heif-image-plugin

Once installed, various image viewers should be able to decode the images.  I rather like nomacs as a fairly tolerable replacement for Irfan Skiljan‘s still awesome irfanview.

Update: 2022-09-22

Jammy isn’t supported by the jakar PPA, but there are a few other options:

Easy, from Hritik Chaudhary in this post,

sudo apt install heif-gdk-pixbuf


should give gdk access, but not (it seems) qt.  You can use gpicview as an imageviewer with this library.

sudo apt install gpicview


Or build the qt-heic-image-plugin from source:

git clone --depth 1 https://github.com/novomesk/qt-heic-image-plugin.git
cd qt-heic-image-plugin
mkdir build
cd build
cmake -DCMAKE_BUILD_TYPE=Release ..
make
sudo make install


This machine required ECM from extra cmake modules, which I hadn’t previously installed.

sudo apt install extra-cmake-modules


to successfully cmake.

Posted at 03:56:36 GMT-0700

Category: HowToLinuxphotoPositivereviewstechnology

# 1976 GMC Suburban

Friday, May 17, 2019

When I was a young child, my dad bought a brand new 1976 GMC Suburban. Yellow. No extras at all – no head liner, plastic seats, manual everything, 305 V8.

It became my car in high school, survived that. Came out to California with me; ended up in the service of SRL, survived that too.

Eventually, it escaped.

Posted at 13:18:33 GMT-0700

Category: photoSRL

# Green Lacewings

Sunday, January 10, 2016

I noticed that my avocado tree was developing brown spots on the leaves, which were almost certainly the result of Persea mites.

So I looked up some possible cures, and it seemed like introducing a predator would be the best option and the least hassle.  I’d had good luck with introduced ladybugs a few years back, which formed a stable population that survived for many years after introduction.  For this pest, green lacewings are recommended.  I found a nearby insectary that could provide larvae on cards and they shipped them overnight.

The little guys look cute just waiting to hatch…

I hung he cards on the leaves of the tree after incubating them overnight in a warm room, and they should hatch sometime in the next day or two, as long as the ants don’t find them first…

Update 8 Sept 2016:

The green lacewings seem to have eaten all the mites.  It has been 9 months and there aren’t any signs of damage to this spring’s leaves.  Yay!

The new leaves that grew seem to be developing without any bites at all.  The old leaves that were too damaged have fallen off, but the surviving older leaves still show the scars of the mites.  Green lacewings seem to have done the trick.

Posted at 14:40:47 GMT-0700

Category: photoPositivereviews

# United’s Magic Trays

Thursday, September 3, 2015

@United has new coach trays that are coated with a material that has an amazing coefficient of friction.  They are not sticky at all—there’s no adhesion effect—it is all friction.  Even low surface energy plastics don’t slide on it at all.

The approximately 75-80° angle in the picture is the point at which the cup topples over itself.  It isn’t adhered to the surface and it doesn’t appear to slide at all before toppling.

This would be the perfect coating for a smart phone pad in a car.

Posted at 11:00:39 GMT-0700

Category: Fabricationphotoplanestechnologytravel

# Summer Blooms

Friday, July 24, 2015

Posted at 13:41:13 GMT-0700

Category: photoweather

# Tortuga Stalking the Yard

Thursday, July 23, 2015

Posted at 01:24:04 GMT-0700

Category: catsphoto

# The Avocado Tree is Fruiting

Tuesday, July 21, 2015

A couple of years back a random sprout appeared in the yard. It looked like a volunteer avocado and grew bizarrely fast. After a few years, it is about 15′ tall and this year it fruited for the first time. It really is an avocado tree.

Posted at 23:15:30 GMT-0700

Category: photo