Welcome
Welcome to My Learning. Downloading and connecting to the app is very easy, just follow the three steps…!
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This example shows how to use a single function to listen to the tap event across multiple map objects held within the same object container.
tap


Reciprocal Feature Learning via Explicit and Implicit Tasks in Scene Text Recognition
Abstract
Text recognition is a popular topic in recent years for its broad applications. In this work, we excavate the implicit task, character counting within the traditional text recognition, without additional labor annotation cost. The implicit task plays as an auxiliary branch for complementing the sequential recognition. We design a two-branch reciprocal feature learning framework in order to adequately utilize the features from both the tasks. Through exploiting the complementary effect between explicit and implicit tasks, the feature is reliably enhanced. Extensive experiments on 7 benchmarks show the advantages of the proposed methods in both text recognition and the new-built character counting tasks. In addition, it is convenient yet effective to equip with variable networks and tasks. We offer abundant ablation studies, generalizing experiments with deeper understanding on the tasks. Code is available. [Paper]Highlights Contributions
❃ We propose a unified framework VSR for document layout analysis, combin- ing vision, semantics and relations.
❃ We dig the implicit task in the traditional STR, i.e., character counting, without any extra annotation cost. The counting network supervised by new ex- ploited labels can be regarded as an auxiliary part in addition to the recognition task, facilitating positive outcomes. Also, we offer a strong baseline for the sole newly-built character counting task based on the existing STR datasets.
❃ We propose a multi-task learning framework called RF-L for STR through exploiting the complementary effect between two different tasks, word recogni- tion and counting respectively. And the two tasks are learned in their own branch, in interaction to the other, via a simple yet effective RF-Adaptor module.
❃ The proposed method achieves impressive improvements in multiple bench- marks, not only in STR tasks but also in counting. The auxiliary network and the adaptor can be easily integrated into deep neural network with any other scene text recognition method, which boosts the single task via the proposed RF-L framework as verified in extensive experiments.
Recommended Citations
If you find our work is helpful to your research, please feel free to cite us:@inproceedings{jiang2021Reciprocal, title={Reciprocal Feature Learning via Explicit and Implicit Tasks in Scene Text Recognition}, author={Jiang, Hui and Xu, Yunlu and Cheng, Zhanzhan and Pu, Shiliang and Niu, Yi and Ren, Wenqi and Wu, Fei and Tan, Wenming}, booktitle = {ICDAR}, volume= {12821}, pages= {287--303}, year={2021}, }


This article is to give you some insight about how I got the Codess internship, what being thrown into the corporate world felt like, and a little about my work life in Hyderabad.
In my fourth semester, I decided to make the most of my summer after my second year, after finally getting into my branch. But If you're a second year, you don't have the opportunity to sit through the placement tests and interviews to land an internship as the third years do. This was when I found out about Codess through my senior.
Codess is a program for female Coders initiated by Microsoft, established in an effort to promote gender diversity and to be inclusive in the engineering field.
Eligibility: Undergraduate 2nd year female students from any branch are eligible for Codess.
Registration links rolled out by the end of February, and everyone who registered had to go through an online assessment test to assess our potential.
Some of the students were selected for a Summer mentorship program which would give you a headstart in your internship process. Another select few would get to visit the MS campus, participate in a hackathon and have a chance to bag a summer internship at Microsoft.
5 students from NITK were selected to travel to the Microsoft campus in Bangalore for a 2-day event in the beginning of March. On the first day, we networked with Microsoft employees as well as students from other campuses. We had a hands-on technology workshop and on the next day, we were divided into teams for a mentored conceptual hackathon. Each team then pitched their ideas to judges, who chose the top four teams to present their ideas to the audience.
Based on our performance for the ideathon, we were offered internships for 8 weeks during the summer after our second year. Even if your team wasn’t in the top four, your individual performance is what will be evaluated, so be sure to do your best!
For the online assessment tests, good logic, basic DSA knowledge and being comfortable with one programming language is sufficient. However, at the MS campus you are judged for your team working ability, creativity, communication and presentation skills. Focus on presenting your genuine, enthusiastic self and it will certainly give you an edge.
I was working in Foundry as a software developer in the Microsoft ISC at Hyderabad. In Foundry, each project is assigned 4 software devs, consisting of two second years and two third years (possibly even a fifth design intern), and this team will be responsible for the development of their project. Each team will have a couple of mentors to guide them in the right direction, and provide them with the necessary resources. The mentors were all extremely helpful and assisted us throughout our internship experience.
As Foundry had a common working space, all the interns were soon interacting and bonding while simultaneously learning and applying their knowledge in their respective projects. There were ‘break areas’, with table tennis and pool tables, a small library and even a karaoke machine!
Interns that were part of Foundry were lucky enough to have a choice in which project they would work on, which I was not expecting. Microsoft’s flexible yet efficient work schedule and attitude to project development allowed us to work without feeling overworked while at the same time ensuring that we don’t underdeliver. The fact that the company took a keen interest in making sure that we had an enriching internship time, even outside the company, was very refreshing.
All in all, the wonderful work culture, talented professionals, and enthusiastic peers all added up to an enriching memorable internship experience!


Visualisation¶
cf-plot¶
The cf-plot package provides
metadata-aware visualisation for cf
fields. This is a separate
library and cf
does not depend on it.
The functionality of cfplot
includes
- Cylindrical projection plots
- Polar stereographic plots
- Latitude/longitude - height plots
- Hovmuller plots
- Vector plots
- Stipple (significance) plots
- Multiple plots on a page
- Different colour scales
- User defined axes
- Rotated pole plots
- Irregular grid plots
- Graph plots
Examples¶
There are many and varied examples of using cf-plot with cf
on the
cf-plot homepage (http://ajheaps.github.io/cf-plot/). Two simple
examples are shown here.
A simple 2-d contour plot could be produced as follows:
>>> import cf
>>> import cfplot
>>> f = cf.read_field('data1.nc')
>>> cfplot.con(f)
A simple 1-d line plot could be produced as follows:
>>> f = cf.read_field('data2.nc')
>>> cfplot.lineplot(f, marker='o', color='blue', title='Zonal mean zonal wind at 100mb')


{% extends "templates/web.html" %} {% block title %} Payments {% endblock %} {%- block page_content -%}
Have we sent you a payment request over email?
Please enter your payment request and reference numbers below to get started


{% include header.html %} RevolutionUC Student Hackathon at the University of Cincinnati March 3rd & 4th, 2018 Join Waitlist Learn More ⌄ {{ content }} {% include footer.html %}
Student Hackathon at the University of Cincinnati
March 3rd & 4th, 2018


We're in the year 2014: Too bad <blink> tags do not work in modern browsers any more...
Using Web Components, you can get it back:
How to?
- Get x-blink.html
from this repository and put it in your directory
- Add the following lines to the head of your document:
<script src="https://cdnjs.cloudflare.com/ajax/libs/polymer/0.3.4/platform.js"></script> <script src="https://cdnjs.cloudflare.com/ajax/libs/polymer/0.3.4/polymer.js"></script> <link rel="import" href="x-blink.html">
- Use <x-blink>Wow, so amazing!</x-blink>
to make the text blink. No more JavaScript needed.
License
MIT License


RADIOLAND MURDERS A film review by Scott Renshaw Copyright 1994 Scott Renshaw
Starring: Mary Stuart Masterson, Brian Benben, Ned Beatty, Michael Lerner, Jeffrey Tambor, Anita Morris, Stephen Tobolowsky. Screenplay: Willard Huyck & Gloria Katz and Jeff Reno & Ron Osborn. Director: Mel Smith.
A couple of years ago, director Barry Levinson made a movie based on a twenty-year-old idea. This pet project was loud, heavy-handed and self-indulgent, and clearly showed why it hadn't been made twenty years earlier: it wasn't a very good idea. However, Levinson had acquired the cachet to make any movie he wanted to make, so he made TOYS. George Lucas has even more cachet, and he also decided to produce a twenty-year-old idea. The result, unfortunately, is similar to TOYS. RADIOLAND MURDERS is an attempt at farce that is simply chaotic and grating, and its frantic pace can't disguise the fact that it just isn't funny.
RADIOLAND MURDERS is set in 1939 at WBN, a Chicago radio station that is planning to launch a fourth national network. On this evening, the station owner (Ned Beatty) is entertaining potential affiliates and a live studio audience with a sampling of the shows the network will offer. However, there is a lot more going on backstage than onstage. Writer Roger Henderson (Brian Benben) is desperately trying to convince his wife Penny (Mary Stuart Masterson), the station's do-everything assistant, that he hasn't been unfaithful; the writing staff is desperately working against the clock to make the changes ordered by the chief sponsor (Brion James). And someone is killing off members of the station staff, with Roger becoming the chief suspect.
For nearly its entire first hour, RADIOLAND MURDERS succeeded primarily in giving me a terrible headache. The story rockets from character to character, lingering just long enough to let us see that each one is defined almost exclusively by a single annoying character trait. The incompetent director (Jeffrey Tambor) has a bad toupee; the station manager (Larry Miller) has a German accent; the head writer (Harvey Korman) is a mush-mouthed drunk; another writer (Bobcat Goldthwait) is...well, Bobcat Goldthwait.  They are also stuck with dialogue that must have had whiskers on it in 1939, like the ever-uproarious "You may think you know what I know, but I don't think you know what you think you know" bit. The slapstick is better, but it too is simply too stale to sustain the energy.
The second half is a significant improvement, focusing on Roger's attempts to stay one step ahead of the police and solve the murders before he himself is arrested for them. Brian Benben (of HBO's "Dream On") is a charming comic actor, and his gifts with physical comedy make a perilous descent down the side of the station building and dressing in a Carmen Miranda get-up far funnier than they have any right to be. But director Mel Smith (THE TALL GUY) makes the horrendous decision to keep cutting away to the performers on stage. Every time he does so, RADIOLAND MURDERS just stops dead, and it's not worth the jerky ride simply to see cameos by Billy Barty, Rosemary Clooney and George Burns. Benben is the best thing RADIOLAND MURDERS has going for it, but Smith doesn't seem to realize it.
Ultimately, that decision is indicative of what is most wrong with RADIOLAND MURDERS: no one seems clear exactly what it is supposed to be. An homage to the days of live radio? A backstage farce a la NOISES OFF? A murder mystery? A romantic comedy? Lucas and his team of screenwriters seem to want it all, and as a result they end up without much of anything. RADIOLAND MURDERS is one of those unfortunate films which equates loud and fast with entertaining, when in reality it's simply noisy and busy.
On the Renshaw scale of 0 to 10 radios: 3.
-- Scott Renshaw Stanford University Office of the General Counsel
.
The review above was posted to the
rec.arts.movies.reviews newsgroup (de.rec.film.kritiken for German reviews).
The Internet Movie Database accepts no responsibility for the contents of the
review and has no editorial control. Unless stated otherwise, the copyright
belongs to the author.
Please direct comments/criticisms of the review to relevant newsgroups.
Broken URLs inthe reviews are the responsibility of the author.
The formatting of the review is likely to differ from the original due
to ASCII to HTML conversion.
Related links: index of all rec.arts.movies.reviews reviews


Potential US presidential candidate Michael Bloomberg spends record amount for TV ads
As per ad tracking firm Advertising Analytics, Michael Bloomberg has purchased a total of $31 million in advertising inserts, the largest sum ever spent by a US presidential candidate.
Billionaire Michael Bloomberg, a potential candidate for 2020 US election, is planning to launch a $31 million television advertising campaign on Monday.
As per ad tracking firm Advertising Analytics, Bloomberg has purchased a total of $31 million in advertising inserts, the largest sum ever spent by a US presidential candidate.
Bernie Sanders, one of the frontrunners in the presidential race, slammed the move in a tweet on Friday and stating he was "disgusted by the idea that Michael Bloomberg or any billionaire thinks they can circumvent the political process and spend tens of millions of dollars to buy elections".
He tweeted that if you can't build grassroot support for your candidacy than "you have no business running for president."
The amount exceeds the record $25 million spent by former US president Barack Obama in 2012 for his campaign and reflects the financial might of one of the richest men in the world.
Bloomberg, a former New York mayor from 2002 to 2013, registered on Thursday with the US Federal Election Commission, a step closer to running for US presidency.
Nearly two weeks ago, Bloomberg said that he was "close" to take a final call on whether to enter the crowded battleground of Democrats for 2020 presidency.
(with inputs from AFP)


{% extends "cms/home.html" %} {% load cms_tags danceschool_tags sekizai_tags static i18n %} {% block content %} {% page_url 'directions' as directions_url %} {% page_url 'calendar' as calendar_url %}
Our upcoming classes have not yet been posted, but don't worry, they will be posted here soon! Check back soon for more information.
{% if calendar_url %}In the meantime, check out our calendar for more information about our past and current classes.
{% endif %} {% elif not allSeries %}Our upcoming classes have not yet been posted, but don't worry, they will be posted here soon! Check back soon for more information.
{% if calendar_url %}In the meantime, check out our calendar for more information about our past and current classes.
{% endif %} {% endif %} {% endblock %} {% if allSeries or allEvents %} {% block registration_form %} {% endblock %}


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: | {{ stats.singleSeasonPerWeek }} |
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Former MP Brian Donohoe hails 'special day' as he collects knighthood
Brian, from Irvine, was awarded a knighthood in the Queen’s Birthday Honours List in recognition of his parliamentary and political work over 23 years.
by Eric McGowan, https://www.dailyrecord.co.uk/authors/eric-mcgowan/Former Cunninghame South and Central Ayrshire MP Brian Donohoe hailed 'a special day' as he collected his knighthood at Buckingham Palace last week.
Sir Brian was joined by wife Christine at an investiture ceremony in which he was conferred with the title Knights Bachelor.
Brian, from Irvine, was awarded a knighthood in the Queen’s Birthday Honours List in recognition of his parliamentary and political work over 23 years.
He served as an MP between 1992 and 2015, latterly in the expanded Central Ayrshire Constituency.
Said Brian: “It was a special day for all my family. I'm really pleased and proud to have been honoured in this way.”


Documents sent
We've sent confirmation to<EMAIL_ADDRESS>| UKPRN | Academy | Document type | Name | ||
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If you've uploaded the wrong document - upload the correct one with the same name and add version 2 and we will associate the two files.
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--- layout: post title: 'Ed''s been busy in the lab...' date: 2004-10-18 00:00:00 category: personal ---


BQN
Notes:
- You can type special characters with a backslash prefix, as shown by hovering over the character bar above. Documentation links for primitives are found here.
- Any modifier with enter will execute (not just shift).
- BQN uses
‿
(backslash-space) for stranding, and not juxtaposition. If you don't know what went wrong, check for this first!
- This implementation is still WIP, and in particular I am improving error checking and messages now. Support for function headers and multiple bodies is missing, and Under (
⌾
) only works for a small class of structural functions. Performance is bad.


Hi! My name’s Ben, I’m a 30-year old interface designer.
You can see some of my recent work on Dribbble.
Feel free to send me an email or ping me on Twitter!
clicking on "h1" removes class "open" on dynamic "h1.open"
clicking on "h1" adds class "open" on "target"


A location in the cloud (or locally) where developers can store code. It allows developers to quickly share their code and work on the same project simultaneously.
Save for later
Devan
Lorem ipsum dolor sit amet, consectetuer adipiscing elit, sed diam nonummy nibh euismod tincidunt ut laoreet dolore magna.
Chad


Tutorial
This tutorial covers the topic of image-based 3D reconstruction by demonstrating the individual processing steps in COLMAP. If you are interested in a more general and mathematical introduction to the topic of image-based 3D reconstruction, please also refer to the CVPR 2017 Tutorial on Large-scale 3D Modeling from Crowdsourced Data and [schoenberger_thesis].
Image-based 3D reconstruction from images traditionally first recovers a sparse representation of the scene and the camera poses of the input images using Structure-from-Motion. This output then serves as the input to Multi-View Stereo to recover a dense representation of the scene.
Quickstart
First, start the graphical user interface of COLMAP, as described here. COLMAP provides an automatic reconstruction tool that simply takes
a folder of input images and produces a sparse and dense reconstruction in a
workspace folder. Click Reconstruction > Automatic Reconstruction
in the GUI
and specify the relevant options. The output is written to the workspace folder.
 The dense point cloud fused.ply
can be imported
in COLMAP using File > Import model from ...
, while the dense mesh must be
visualized with an external viewer such as Meshlab.
The following sections give general recommendations and describe the reconstruction process in more detail, if you need more control over the reconstruction process/parameters or if you are interested in the underlying technology in COLMAP.
Structure-from-Motion
Structure-from-Motion (SfM) is the process of reconstructing 3D structure from its projections into a series of images. The input is a set of overlapping images of the same object, taken from different viewpoints. The output is a 3-D reconstruction of the object, and the reconstructed intrinsic and extrinsic camera parameters of all images. Typically, Structure-from-Motion systems divide this process into three stages:
Feature detection and extraction
Feature matching and geometric verification
Structure and motion reconstruction
COLMAP reflects these stages in different modules, that can be combined depending on the application. More information on Structure-from-Motion in general and the algorithms in COLMAP can be found in [schoenberger16sfm] and [schoenberger16mvs].
If you have control over the picture capture process, please follow these guidelines for optimal reconstruction results:
Capture images with good texture. Avoid completely texture-less images (e.g., a white wall or empty desk). If the scene does not contain enough texture itself, you could place additional background objects, such as posters, etc.
Capture images at similar illumination conditions. Avoid high dynamic range scenes (e.g., pictures against the sun with shadows or pictures through doors/windows). Avoid specularities on shiny surfaces.
Capture images with high visual overlap. Make sure that each object is seen in at least 3 images – the more images the better.
Capture images from different viewpoints. Do not take images from the same location by only rotating the camera, e.g., make a few steps after each shot. At the same time, try to have enough images from a relatively similar viewpoint. Note that more images is not necessarily better and might lead to a slow reconstruction process. If you use a video as input, consider down-sampling the frame rate.
Multi-View Stereo
Multi-View Stereo (MVS) takes the output of SfM to compute depth and/or normal information for every pixel in an image. Fusion of the depth and normal maps of multiple images in 3D then produces a dense point cloud of the scene. Using the depth and normal information of the fused point cloud, algorithms such as the (screened) Poisson surface reconstruction [kazhdan2013] can then recover the 3D surface geometry of the scene. More information on Multi-View Stereo in general and the algorithms in COLMAP can be found in [schoenberger16mvs].
Preface
COLMAP requires only few steps to do a standard reconstruction for a general
user. For more experienced users, the program exposes many different parameters,
only some of which are intuitive to a beginner. The program should usually work
without the need to modify any parameters. The defaults are chosen as a trade-
off between reconstruction robustness/quality and speed. You can set “optimal”
options for different reconstruction scenarios by choosing Extras > Set
options for ... data
. If in doubt what settings to choose, stick to the
defaults. The source code contains more documentation about all parameters.
COLMAP is research software and in rare cases it may exit ungracefully if some constraints are not fulfilled. In this case, the program prints a traceback to stdout. To see this traceback or more debug information, it is recommended to run the executables (including the GUI) from the command-line, where you can define various levels of logging verbosity.
Terminology
The term camera is associated with the physical object of a camera using the same zoom-factor and lens. A camera defines the intrinsic projection model in COLMAP. A single camera can take multiple images with the same resolution, intrinsic parameters, and distortion characteristics. The term image is associated with a bitmap file, e.g., a JPEG or PNG file on disk. COLMAP detects keypoints in each image whose appearance is described by numerical descriptors. Pure appearance-based correspondences between keypoints/descriptors are defined by matches, while inlier matches are geometrically verified and used for the reconstruction procedure.
Data Structure
COLMAP assumes that all input images are in one input directory with potentially nested sub-directories. It recursively considers all images stored in this directory, and it supports various different image formats (see FreeImage). Other files are automatically ignored. If high performance is a requirement, then you should separate any files that are not images. Images are identified uniquely by their relative file path. For later processing, such as image undistortion or dense reconstruction, the relative folder structure should be preserved. COLMAP does not modify the input images or directory and all extracted data is stored in a single, self-contained SQLite database file (see Database Format).
The first step is to start the graphical user interface of COLMAP by running the
pre-built binaries (Windows: COLMAP.bat, Mac: COLMAP.app) or by executing
./src/colmap/exe/colmap gui
from the CMake build folder. Next, create a new project
by choosing File > New project
. In this dialog, you must select where to
store the database and the folder that contains the input images. For
convenience, you can save the entire project settings to a configuration file by
choosing File > Save project
. The project configuration stores the absolute
path information of the database and image folder in addition to any other
parameter settings. If you decide to move the database or image folder, you must
change the paths accordingly by creating a new project. Alternatively, the
resulting .ini configuration file can be directly modified in a text editor of
your choice. To reopen an existing project, you can simply open the
configuration file by choosing File > Open project
and all parameter
settings should be recovered. Note that all COLMAP executables can be started
from the command-line by either specifying individual settings as command-line
arguments or by providing the path to the project configuration file (see
Interface).
An example folder structure could look like this:
/path/to/project/...
+── images
│ +── image1.jpg
│ +── image2.jpg
│ +── ...
│ +── imageN.jpg
+── database.db
+── project.ini
In this example, you would select /path/to/project/images as the image folder path, /path/to/project/database.db as the database file path, and save the project configuration to /path/to/project/project.ini.
Feature Detection and Extraction
In the first step, feature detection/extraction finds sparse feature points in the image and describes their appearance using a numerical descriptor. COLMAP imports images and performs feature detection/extraction in one step in order to only load images from disk once.
Next, choose Processing > Extract features
. In this dialog, you must first
decide on the employed intrinsic camera model. You can either automatically
extract focal length information from the embedded EXIF information or manually
specify intrinsic parameters, e.g., as obtained in a lab calibration. If an
image has partial EXIF information, COLMAP tries to find the missing camera
specifications in a large database of camera models automatically. If all your
images were captured by the same physical camera with identical zoom factor, it
is recommended to share intrinsics between all images. Note that the program
will exit ungracefully if the same camera model is shared among all images but
not all images have the same size or EXIF focal length. If you have several
groups of images that share the same intrinsic camera parameters, you can easily
modify the camera models at a later point as well (see Database Management). If in doubt what to choose in this step, simply stick
to the default parameters.
You can either detect and extract new features from the images or import existing features from text files. COLMAP extracts SIFT [lowe04] features either on the GPU or the CPU. The GPU version requires an attached display, while the CPU version is recommended for use on a server. In general, the GPU version is favorable as it has a customized feature detection mode that often produces higher quality features in the case of high contrast images. If you import existing features, every image must have a text file next to it (e.g., /path/to/image1.jpg and /path/to/image1.jpg.txt) in the following format:
NUM_FEATURES 128
X Y SCALE ORIENTATION D_1 D_2 D_3 ... D_128
...
X Y SCALE ORIENTATION D_1 D_2 D_3 ... D_128
where X, Y, SCALE, ORIENTATION are floating point numbers and D_1…D_128 values in the range 0…255. The file should have NUM_FEATURES lines with one line per feature. For example, if an image has 4 features, then the text file should look something like this:
4 128
1.2 2.3 0.1 0.3 1 2 3 4 ... 21
2.2 3.3 1.1 0.3 3 2 3 2 ... 32
0.2 1.3 1.1 0.3 3 2 3 2 ... 2
1.2 2.3 1.1 0.3 3 2 3 2 ... 3
Note that by convention the upper left corner of an image has coordinate (0, 0) and the center of the upper left most pixel has coordinate (0.5, 0.5). If you must import features for large image collections, it is much more efficient to directly access the database with your favorite scripting language (see Database Format).
If you are done setting all options, choose Extract
and wait for the
extraction to finish or cancel. If you cancel during the extraction process, the
next time you start extracting images for the same project, COLMAP automatically
continues where it left off. This also allows you to add images to an existing
project/reconstruction. In this case, be sure to verify the camera parameters
when using shared intrinsics.
All extracted data will be stored in the database file and can be reviewed/managed in the database management tool (see Database Management) or, for experts, directly modified using SQLite (see Database Format).
Feature Matching and Geometric Verification
In the second step, feature matching and geometric verification finds correspondences between the feature points in different images.
Please, choose Processing > Match features
and select one of the provided
matching modes, that are intended for different input scenarios:
Exhaustive Matching: If the number of images in your dataset is relatively low (up to several hundreds), this matching mode should be fast enough and leads to the best reconstruction results. Here, every image is matched against every other image, while the block size determines how many images are loaded from disk into memory at the same time.
Sequential Matching: This mode is useful if the images are acquired in sequential order, e.g., by a video camera. In this case, consecutive frames have visual overlap and there is no need to match all image pairs exhaustively.  This matching mode has built-in loop detection based on a vocabulary tree, where every N-th image (loop_detection_period) is matched against its visually most similar images (loop_detection_num_images). Note that image file names must be ordered sequentially (e.g., image0001.jpg, image0002.jpg, etc.). The order in the database is not relevant, since the images are explicitly ordered according to their file names. Note that loop detection requires a pre-trained vocabulary tree, that can be downloaded from https://demuc.de/colmap/.
Vocabulary Tree Matching: In this matching mode [schoenberger16vote], every image is matched against its visual nearest neighbors using a vocabulary tree with spatial re-ranking. This is the recommended matching mode for large image collections (several thousands). This requires a pre-trained vocabulary tree, that can be downloaded from https://demuc.de/colmap/.
Spatial Matching: This matching mode matches every image against its spatial nearest neighbors. Spatial locations can be manually set in the database management. By default, COLMAP also extracts GPS information from EXIF and uses it for spatial nearest neighbor search. If accurate prior location information is available, this is the recommended matching mode.
Transitive Matching: This matching mode uses the transitive relations of already existing feature matches to produce a more complete matching graph. If an image A matches to an image B and B matches to C, then this matcher attempts to match A to C directly.
Custom Matching: This mode allows to specify individual image pairs for matching or to import individual feature matches. To specify image pairs, you have to provide a text file with one image pair per line:
image1.jpg image2.jpg image1.jpg image3.jpg ...
where image1.jpg is the relative path in the image folder. You have two options to import individual feature matches. Either raw feature matches, which are not geometrically verified or already geometrically verified feature matches. In both cases, the expected format is:
image1.jpg image2.jpg 0 1 1 2 3 4 <empty-line> image1.jpg image3.jpg 0 1 1 2 3 4 4 5 <empty-line> ...
where image1.jpg is the relative path in the image folder and the pairs of numbers are zero-based feature indices in the respective images. If you must import many matches for large image collections, it is more efficient to directly access the database with a scripting language of your choice.
If you are done setting all options, choose Match
and wait for the matching
to finish or cancel in between. Note that this step can take a significant
amount of time depending on the number of images, the number of features per
image, and the chosen matching mode. Expected times for exhaustive matching are
from a few minutes for tens of images to a few hours for hundreds of images to
days or weeks for thousands of images. If you cancel the matching process or
import new images after matching, COLMAP only matches image pairs that have not
been matched previously. The overhead of skipping already matched image pairs is
low. This also enables to match additional images imported after an initial
matching and it enables to combine different matching modes for the same
dataset.
All extracted data will be stored in the database file and can be reviewed/managed in the database management tool (see Database Management) or, for experts, directly modified using SQLite (see Database Format).
Note that feature matching requires a GPU and that the display performance of your computer might degrade significantly during the matching process. If your system has multiple CUDA-enabled GPUs, you can select specific GPUs with the gpu_index option.
Sparse Reconstruction
After producing the scene graph in the previous two steps, you can start the
incremental reconstruction process by choosing Reconstruction > Start
.
COLMAP first loads all extracted data from the database into memory and seeds
the reconstruction from an initial image pair. Then, the scene is incrementally
extended by registering new images and triangulating new points. The results are
visualized in “real-time” during this reconstruction process. Refer to the
Graphical User Interface section for more details about the
available controls. COLMAP attempts to reconstruct multiple models if not all
images are registered into the same model. The different models can be selected
from the drop-down menu in the toolbar. If the different models have common
registered images, you can use the model_converter
executable to merge them
into a single reconstruction (see FAQ for details).
Ideally, the reconstruction works fine and all images are registered. If this is not the case, it is recommended to:
Perform additional matching. For best results, use exhaustive matching, enable guided matching, increase the number of nearest neighbors in vocabulary tree matching, or increase the overlap in sequential matching, etc.
Manually choose an initial image pair, if COLMAP fails to initialize. Choose
Reconstruction > Reconstruction options > Init
and set images from the database management tool that have enough matches from different viewpoints.
Importing and Exporting
COLMAP provides several export options for further processing. For full
flexibility, it is recommended to export the reconstruction in COLMAP’s data
format by choosing File > Export
to export the currently viewed model or
File > Export all
to export all reconstructed models. The model is exported
in the selected folder using separate text files for the reconstructed cameras,
images, and points. When exporting in COLMAP’s data format, you can re- import
the reconstruction for later visualization, image undistortion, or to continue
an existing reconstruction from where it left off (e.g., after importing and
matching new images). To import a model, choose File > Import
and select the
export folder path. Alternatively, you can also export the model in various
other formats, such as Bundler, VisualSfM [1], PLY, or VRML by choosing
File > Export as...
. COLMAP can visualize plain PLY point cloud files with
RGB information by choosing File > Import From...
. Further information about
the format of the exported models can be found here.
Dense Reconstruction
After reconstructing a sparse representation of the scene and the camera poses of the input images, MVS can now recover denser scene geometry. COLMAP has an integrated dense reconstruction pipeline to produce depth and normal maps for all registered images, to fuse the depth and normal maps into a dense point cloud with normal information, and to finally estimate a dense surface from the fused point cloud using Poisson [kazhdan2013] or Delaunay reconstruction.
To get started, import your sparse 3D model into COLMAP (or select the
reconstructed model after finishing the previous sparse reconstruction steps).
Then, choose Reconstruction > Multi-view stereo
and select an empty or
existing workspace folder, which is used for the output and of all dense
reconstruction results. The first step is to undistort
the images, second to
compute the depth and normal maps using stereo
, third to fuse
the depth
and normals maps to a point cloud, followed by a final, optional point cloud
meshing
step. During the stereo reconstruction process, the display might
freeze due to heavy compute load and, if your GPU does not have enough memory,
the reconstruction process might ungracefully crash. Please, refer to the FAQ
(freeze and memory) for
information on how to avoid these problems. Note that the reconstructed normals
of the point cloud cannot be directly visualized in COLMAP, but e.g. in Meshlab
by enabling Render > Show Normal/Curvature
. Similarly, the reconstructed
dense surface mesh model must be visualized with external software.
In addition to the internal dense reconstruction functionality, COLMAP exports
to several other dense reconstruction libraries, such as CMVS/PMVS [furukawa10]
or CMP-MVS [jancosek11]. Please choose Extras > Undistort images
and select
the appropriate format. The output folders contain the reconstruction and the
undistorted images. In addition, the folders contain sample shell scripts to
perform the dense reconstruction. To run PMVS2, execute the following commands:
./path/to/pmvs2 /path/to/undistortion/folder/pmvs/ option-all
where /path/to/undistortion/folder is the folder selected in the undistortion dialog. Make sure not to forget the trailing slash in /path/to/undistortion/folder/pmvs/ in the above command-line arguments.
For large datasets, you probably want to first run CMVS to cluster the scene into more manageable parts and then run COLMAP or PMVS2. Please, refer to the sample shell scripts in the undistortion output folder on how to run CMVS in combination with COLMAP or PMVS2. Moreover, there are a number of external libraries that support COLMAP’s output:
Database Management
You can review and manage the imported cameras, images, and feature matches in
the database management tool. Choose Processing > Manage database
. In the
opening dialog, you can see the list of imported images and cameras. You can
view the features and matches for each image by clicking Show image
and
Overlapping images
. Individual entries in the database tables can be
modified by double clicking specific cells. Note that any changes to the
database are only effective after clicking Save
.
To share intrinsic camera parameters between arbitrary groups of images, select
a single or multiple images, choose Set camera
and set the camera_id,
which corresponds to the unique camera_id column in the cameras table. You can
also add new cameras with specific parameters. By setting the
prior_focal_length flag to 0 or 1, you can give a hint whether the
reconstruction algorithm should trust the focal length value. In case of a prior
lab calibration, you want to set this value to 1. Without prior knowledge about
the focal length, it is recommended to set this value to 1.25 *
max(width_in_px, height_in_px).
The database management tool has only limited functionality and, for full control over the data, you must directly modify the SQLite database (see Database Format). By accessing the database directly, you can use COLMAP only for feature extraction and matching or you can import your own features and matches to only use COLMAP’s incremental reconstruction algorithm.
Graphical and Command-line Interface
Most of COLMAP’s features are accessible from both the graphical and the
command-line interface, which are both embedded in the same executable. You can
provide the options directly as command-line arguments or you can provide a
.ini project configuration file containing the options using the
--project_path path/to/project.ini
argument. To start the GUI application,
please execute colmap gui
or directly specify a project configuration as
colmap gui --project_path path/to/project.ini
to avoid tedious selection in
the GUI. To list the different commands available from the command-line, execute
colmap help
. For example, to run feature extraction from the command-line,
you must execute colmap feature_extractor
. The graphical user
interface and command-line Interface sections provide more
details about the available commands.
Footnotes


Learning the structure of RNA expression variation
Table of Contents
Introduction
Characterizing the extent of RNA expression variation within cell types, cell states, donors, and experimental conditions is important to learn about evolutionary constraint on gene regulation, modulation of differentiation potential, and the mechanisms underlying cell fate decisions. However, actually estimating the level of expression variation from scRNA-seq data is difficult. Here, we review some of these difficulties. \( \DeclareMathOperator\Gam{Gamma} \DeclareMathOperator\N{\mathcal{N}} \DeclareMathOperator\Pois{Poisson} \DeclareMathOperator\V{V} \newcommand\mf{\mathbf{F}} \newcommand\mh{\mathbf{H}} \newcommand\mi{\mathbf{I}} \newcommand\ml{\mathbf{L}} \newcommand\vl{\mathbf{l}} \newcommand\vx{\mathbf{x}} \newcommand\vz{\mathbf{z}} \newcommand\vmu{\boldsymbol{\mu}} \newcommand\vphi{\boldsymbol{\phi}} \newcommand\vpi{\boldsymbol{\pi}} \)
Setup
import anndata import numpy as np import mpebpm.topics import scanpy as sc import scipy.stats as st import torch
%matplotlib inline %config InlineBackend.figure_formats = set(['retina'])
import colorcet import matplotlib.pyplot as plt plt.rcParams['figure.facecolor'] = 'w' plt.rcParams['font.family'] = 'Nimbus Sans'
Main results
Pre-defined conditions/hard clustering
The simplest case to consider is analyzing scRNA-seq observations from a single gene in one condition. Then, one can fit an observation model (Sarkar and Stephens 2020)
\begin{align} x_i \mid s_i, \lambda_i &\sim \Pois(s_i \lambda_i), \qquad i = 1, \ldots, n\\ \lambda_i &\sim g = \Gam(\phi^{-1}, \mu^{-1}\phi^{-1}). \end{align}Under this model, it is clear that the variance of true gene expression levels is \(\V[g] = \mu^2\phi\). More generally, one could instead assume that \(g\) belongs to some other family, but still characterize expression variance as \(\V[g]\). There is some evidence that families more flexible than Gamma distributions may be required for a large fraction of genes in some data sets (Sarkar and Stephens 2020). One goal of this analysis is to potentially interpret gene expression variance relative to the mean as indicative of the underlying kinetic parameters of transcriptional bursting.
In the case where \(K\) conditions were pre-defined (e.g., donor) or are learned from the data by hard-clustering, one can readily generalize the above observation model to multiple genes and conditions (Sarkar et al. 2019)
\begin{align} x_{ij} \mid s_i, \lambda_{ij} &\sim \Pois(s_i \lambda_{ij}), \qquad i = 1, \ldots, n; j = 1, \ldots, p\\ \lambda_{ij} &= \mu_{ij} u_{ij}\\ \mu_{ij} &= \exp((\ml\mf')_{ij})\\ u_{ij} \mid \ml, \mh &\sim \Gam(\exp(-(\ml\mh')_{ij}), \exp(-(\ml\mh')_{ij})), \end{align}where \(\ml\) is an \(n \times K\) fixed, binary matrix corresponding to assignment of samples to conditions, \(\mf\) is a \(K \times p\) matrix of mean parameters, and \(\mh\) is a \(K \times p\) matrix of dispersion parameters. This observation model can be readily fit to massive data using stochastic gradient descent. Marginalizing,
\begin{equation} \lambda_{ij} \sim g_{ij}(\cdot) = \Gam(\exp(-(\ml\mh')_{ij}), \exp(-(\ml(\mf + \mh)')_{ij})), \end{equation}where \(g_{ij}\) is identical for observations from the same condition and gene. Therefore, the variance of gene expression can still be estimated as the distinct \(\V[g_{ij}]\). However, this approach has important limitations: (1) it requires pre-defining conditions, which may not be justified by the data (in the case of learning clusters), and (2) it treats every gene independently, and does not consider propagation of noise in gene regulatory networks (e.g., Thattai and van Oudenaarden 2001).
Generalizing to soft clustering
Considering the expression model
\begin{equation} \lambda_{ij} \mid \ml, \mf, \mh \sim \Gam(\exp(-(\ml\mh')_{ij}), \exp(-(\ml(\mf + \mh)')_{ij})), \end{equation}what happens when \(\ml\) is not binary? Suppose \(\ml\) is normalized so that its rows sum to 1; then, this model corresponds to a sort of “noisy topic model,” where topics are characterized by a collection of Gamma distributions for each gene, and cells are convex combinations of those topics. In some sense then, the topics in this model could be thought of as “noisy gene expression programs”. One can in principle fit this model by automatic differentiation and gradient descent, ensuring the sum constraint by re-parameterizing \(\vl_i = \operatorname{softmax}(\tilde{\vl}_i)\). One could also amortize inference by introducing an inference network mapping \(\vx_i\) to \(\vl_i\).
Remark. When \(\ml\) is binary, using the exponential inverse link function makes sense since we are selecting a single log mean parameter and a single log dispersion parameter for each observation. However, when \(\ml\) is instead normalized to have row sum 1, it is not clear that this model makes sense compared to a model with identity link, analogous to NMF/pLSI.
This approach addresses the issues that pre-defined conditions are not always available, and hard-clustering data may not be justified. However, it complicates the question of what precisely the variance of gene expression corresponds to in the model. If we think of samples as being mixtures of gene expression programs, then even the question of what “variance of gene expression” means is problematic, since it is no longer clear what subset of samples the variance is being computed over. Is the variance of each learned gene expression program instead the relevant quantity, regardless of which samples express it? Is this the correct way to think about asking the question when we don’t begin from the assumption that there were some number of distinct cell types present?
In this model, we can think of \(\vl_i\) as a latent variable, and the model above as a linear latent variable model. But now, expression variation has components \(\V[\vl_i]\) and \(\V[\lambda_{ij} \mid \vl_i]\). Which of these components corresponds to expression noise? What does it mean for \(\V[\lambda_{ij} \mid \vl_i] \neq 0\) when \(\vl_i\) is a latent variable for a single observation? When \(\vl_i\) is constrained to lie in the simplex, what does \(\V[\vl_i]\) even mean?
Remark. This model is a generalization of a simple model-based clustering method, in which hard clusters are defined by a collection of Gamma distributions
\begin{equation} \lambda_{ij} \mid \vpi_i, \vmu_k, \vphi_k \sim \sum_{k=1}^{K} \pi_{ik} \Gam(\phi_{kj}^{-1}, \phi_{kj}^{-1}\mu_{kj}^{-1}). \end{equation}It also generalizes other methods (scNBMF, LDVAE), which fit expression models of the form
\begin{align} \lambda_{ij} &= \mu_{ij} u_{ij}\\ \mu_{ij} &= \exp((\ml\mf')_{ij})\\ u_{ij} \mid \phi_j &\sim \Gam(\phi_j^{-1}, \phi_j^{-1}), \end{align}i.e., where \(p(u_{ij})\) is constant across conditions. It is also a related to DCA, which fits a similar expression model, but does not constrain \(\vl_i\) to be in the simplex and assumes a non-linear mapping from \(\vl_i\) to mean and dispersion parameters per cell per gene .
Generalizing to a non-linear latent variable model
Now consider the non-linear latent variable model
\begin{align} x_{ij} \mid s_i, \lambda_{ij} &\sim \Pois(s_i \lambda_{ij})\\ \lambda_{ij} &= (f(\vz_i))_j\\ \vz_i &\sim \N(0, \mi). \end{align}Here, \(f\) is a fully-connected neural network, and variability is pushed into the \(\vz_i\). In this model, expression noise is completely explained by \(\V[\vz_i \mid \vx_i]\). That is, variation in expression levels is completely explained by variation in a low-dimensional latent space. Is this a reasonable model? One thing that isn’t obvious is what exactly expression variance corresponds to in this model, since it is not clear which subset of samples the variance is being computed over. Naively, one could return to hard-clustering the \(\vz_i\), but it is not clear that this is an improvement over existing hard-clustering approaches.
Existing methods (scVI, totalVI) fit an even more complex expression model
\begin{align} \lambda_{ij} &= \mu_{ij} u_{ij}\\ \mu_{ij} &= (f(\vz_i))_j\\ u_{ij} &\sim \Gam(\phi_j^{-1}, \phi_j^{-1})\\ \vz_i &\sim \N(0, \mi). \end{align}In this model, expression noise depends both on variation in the latent space and extra variability. Does this make sense?


StreamLikeSequence Back StreamLikeSequence (constructor) Instance methods lines StreamLikeSequence StreamLikeSequence A StreamLikeSequence comprises a sequence of 'chunks' of data, which are typically multiline strings. lines StreamLikeSequence#lines


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Preparation time
less than 30 mins
Cooking time
30 mins to 1 hour
Serves
Serves 4-6
Dietary
Fresh, sweet peas combined with luxurious fat grains of rice makes for an exceptional spring dish, with just enough heartiness if the weather isn’t yet that warm. For the pea pod stock, blanching the pods is essential to transform their bitter raw taste into a beautiful clean pea flavour.
Equipment and preparation: for this recipe you will need a food processor that can blend ice.
Start by making the pea stock. In a large pan of simmering water, blanch the pea pod shells for 1 minute. Using a slotted spoon, remove the blanched shells and refresh them in the iced water. (This keeps the colour and freshness.)
Once cooled, blend the iced water and pea pods in a food processor until smooth. Strain through a fine sieve. Set aside 100ml/3½fl oz to make the pea purée and the remaining 500ml/18fl oz to make the risotto. (Add water to make the volume up to 500ml/18fl oz if necessary.)
For the pea purée. In a small saucepan on a medium heat, cook the peas in the butter for 5 minutes, adding a pinch of salt. Add the 100ml/3½fl oz reserved pea stock, bring to a boil and simmer for 4 minutes. Transfer to a blender or food processor, blend until smooth and leave to cool.
For the risotto, in a medium saucepan on a low heat, gently fry the onion in the olive oil with a pinch of salt for 2 minutes, until translucent. Add the garlic. Stir in the rice and continue to cook for 3 minutes, until the grains appear shiny (this will give flavour and prevent them sticking together).
Pour in the wine, then 500ml/18fl oz reserved pea stock, stir and bring to the gentlest simmer with only one bubble breaking the surface every minute. Season with salt and pepper then cover with a lid and cook for 20 minutes. Check every now and again that it is not boiling.
After 20 minutes examine a grain of rice and check for a tiny speck of white starch in the middle. This means the risotto is nearly cooked. Stir the rice quickly for 5 minutes to achieve a creamy consistency.
Stir in 200ml/7fl oz cooled pea purée and the Parmesan. Season to taste and set aside.
For the vegetables, in a small saucepan on a high heat, bring the butter, 50ml/2fl oz water and a pinch of salt to the boil. Add the courgettes, cover with a lid and cook on a high heat for 30 seconds, then add the peas, radishes, radish tops and spinach, cover again and cook for 20 seconds. Drain and set aside.
To finish the risotto, stir in the lemon juice and olive oil. Taste and adjust the seasoning. Add a dash of white wine to sharpen the flavour if desired.
Serve the risotto in a large dish topped with the vegetables, blanched pea shoots and a few shavings of Parmesan.


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It is always good practice to confirm with the user when he/she is trying to execute a destructive action. In such situations, the action of type 'confirm' becomes handy. It raises a confirmation dialog to the user.
Within the actions of type 'alert', 'confirm' and 'prompt' an element of name 'message' is used to define the message that the user will be prompted with. Again, a substitution parameter of '?NAME?' is used to substitute in the name of the task. The return code for actions of these types is 'true' for an 'OK' button click and 'false' wither for a click on the 'Cancel' button or the user hitting the window close.
As an action will only occur on 'OK' being clicked, a follow-on action will execute on the return code of this action containing the value 'true'.


Jamaican stars Chris Martin, D Major and Future Fambo light up Nairobi in a fun filled Concert [Photos]
by brian orutaNot even rain could stop them!
Jamaican Stars Chris Martin, D Major and Future Fambo treated Nairobians to a fun filled concert on Saturday.
The three headlined the Big Deal Concert held at the Impala Grounds in Nairobi with Chris Martin who was the main act for the night treating fans to a one and a half hours performance. The crowd in attendance had indeed been waiting for the man of the day, as most of them sang along to the weekend love maker’s favorite songs.
The songs included; Mi Friend Dem, Pirates of The Caribbean, It is love, Let Her Go, Glow, Steppin, Take My Love and Baby I love you among others.
Towards the end of his performance, Chris Martin brought on stage Nigerian singer Ketchup as a surprise act and he entertained revelers with his hit song Pam Pam.
D Major who was part of the main act entertained revelers with some of his best hits, as he gave a 40 minutes performance at the Big Deal Concert.
He treated the party goers to songs like; Live it up, Deal is done, That’s what love is about, Real knows real and Girl of my dreams among other songs.
Also putting a memorable performance was Future Fambo who served revelers to tunes like; Boom special, how we’re living and tonight we’re raving, as he pulled 25 minute performance.
The event emceed by Tallia Oyando and MC Philipo also saw Kenyan acts like Sol Generations Bensoul, KRG the Don, J Fam, Masauti and Elani pulling up memorable performances, despite the heavy downpour that was experienced.
Hypeman Guddah Man entertained the party goes at Impala Club in a hype set, as a host of other DJs also had a chance to make the night worthwhile for revelers.
Photos;


Distribution of density of Na + (a) and Cl (b) near the interface with various n w and n c, where the vertical dash line marks the epitaxial lattice position. n w denotes the number of water molecules in the first hydration shell, and n c is the number of the nearest counter ions.


20 Nov 2016 I'm back? Blog is up on Github! I'm trying this out. Need to get the script issue worked out but I'm closer. Edit: Got it worked out, now I need a background...
10 Nov 2016 Delay Incoming Quick update Won't be posting for a bit because I'm still not sure if I want to pay the monthly fee for the Ghost blog hosting. There are options but...
22 Oct 2016 On That Midnight Train to Georgia I've seen a sign. Here it is: Now, on to business... It was a hell of a week. Aside from that, I got some cool pictures. A friend of mine...
18 Oct 2016 What to do? What to do. I make things difficult for myself. I'm a perfectionist. It's what I do. This new venture is no different. What should I use for a blog theme? Should I get...
16 Oct 2016 Hello! My name is Mark Stringer and I am the Impromptu Artist. This is a work in progress blog that will be developed over time. Stick around for a while!...


Famo.us
No Speed Limits
This is me...
- Hannah Howard
- @techgirlwonder
-<EMAIL_ADDRESS>My Crew:
Logical Reality Design
- www.lrdesign.com
- @lrdesign
- Hire Us!
The Plan
- What is famo.us?
- What can it do?
- How does it work?
- Famo.us Angular
- Concerns
- Let's look at some code
What would the web development of your dreams look like?
What if you weren’t confined to boxes and rectangles?
or 2d-anything really
What if you could use real world physics to animate your web pages?
Famo.us is an advanced rendering platform for the web
How does Famo.us work?
- Express user interface with Javascript instead of HTML
- Build layout with 3D scene graph instead of CSS and DOM
- Express animations with advanced curves and physics
- famo.us translates your code to fast HTML markup
You may have heard things like..
- famo.us makes web perform like native!
- I heard they remade Facebook’s Paper app in like 3 days on famo.us!
- famo.us is going to save the web on mobile!
- famo.us cured world hunger!
But how does it really work?
Let's talk about a scene graph.
At this point in the presentation we did an interactive exercise to illustrate how a scene graph describes an arrangement of objects in 3D space.
Famo.us Internal Tricks
- Update 60 times a second using requestAnimationFrame
- Absolute position everything
- Use CSS3 matrix3d transform layout each element.
A rectangle
var Engine = require('famous/core/Engine');
var Surface = require('famous/core/Surface');
var Transform = require('famous/core/Transform');
var StateModifier = require('famous/modifiers/StateModifier');
var mainContext = Engine.createContext();
var stateModifier = new StateModifier({
transform: Transform.translate(150, 100, 0)
});
var surface = new Surface({
size: [100, 100],
properties: {
backgroundColor: '#FA5C4F'
}
});
mainContext.add(stateModifier).add(surface);
I gotta do all that to get a freakin <div>?
famo.us gives you a lot
but you have to throw out what you already know
famo.us Angular
- Describe famo.us layout using directives
- $compile used to assemble directives into famo.us objects
- Actual visible html rendered by famo.us
Plus you get the other Angular good stuff...
...like Data-binding
...and MVC architecture
$scope.translate = [150, 100, 0];
$scope.size = [100,000]
Can't I do all this with a whole ton of CSS3?
You could.
You could also write all your software with assembler.
Famo.us provides
organization + math
to create fast, awesome, animated interfaces
What about WebGL and Canvas?
WebGL and Canvas are awesome
But they aren't super widely supported
Mixed Mode
The future of famo.us
famo.us will combine DOM and WebGL in a single unified interface
* Works with Famo.us Angular
I gotta troll this one...
But Famo.us is a promise...
..about how good web development could be tomorrow
THE END.
Let's look at some code.


This demo shows you can center multiple types of content :
Text
Images
Lists
98%
3.9/5
Responsive image.
Responsive image.
Responsive image.
Centered responsive images as background with centered content over it.
Again
And again


lociLocations.pl - A program to retrieve chromosomal locations by name
lociLocations.pl [--help] [--locusColumn=columnName] [--path=path of database] [--locilistPath=locilistPath] [--retrieveLoci=loci names] [--anonymous] [--calculateGaps] [--aliases=aliasesPath] [--source=name]
This program takes a list of markers and retrieves the physical and cytogenetic locations from a database. If called with the option --calculateGaps it calculates a histogram of gaps for a given marker set. This allows to check for the saturation of the genome by the given marker set. The loci to be retrieved either from STDIN or from a file specified by the --locilist option. This input is expected to be a tab separated file (see options --locus, --anonymous).
Program output is printed to STDOUT and is in PropertyList format. A dictionary is produced holding as keys the loci names. The values are dictionaries again containing physical (key p) and cytongenetic (key band) information. You can redirect to a file and may directly use it with the --labelMap option of coloredChromosomes.pl.
The default source for retrieval is ENSEMBL as of package version 1.4.2. You need to install the ENSEMBL API as described in http://www.ensembl.org/Docs/linked_docs/ensembl_tutorial.pdf . The source argument of lociLocation is intepreted as follows: --source host:user:db and defaults to 'ensembldb.ensembl.org:anonymous:homo_sapiens_core_29_35b'. Since database versions change frequently and old versions become unavailable you should use the most recent numbers from http://www.ensembl.org/Homo_sapiens. If, for example the web page reads 'Current Release 29.35b' than the database name should be 'homo_sapiens_core_29_35b'. This is clearly a shortcoming in the ENSEMBL database structure where a reference to the current version is lacking. Another problem is that only gene symbols are allowed right now. There is no mechanism to retrieve microsatellite markers. If either of these things do bother you please send an email to<EMAIL_ADDRESS>(as did I). Hopefully this gives momentum to required code changes at EMBL.
coloredChromosomes.pl(1) PropertyList(3)


EYES WIDE SHUT
Reviewed by Harvey Karten, Ph.D. Warner Bros. Director: Stanley Kubrick Writer: Stanley Kubrick, Frederic Raphael, novel "Traumnovelle" by Arthur Schnitzler Cast: Tom Cruise, Nicole Kidman, Sydney Pollack, Todd Field, Marie Richardson, Alan Cumming, Thomas Gibson, Clarke Hayes, Rade Sherbedgia, Vinessa Shaw, Leelee Sobieski
Human beings have roamed the earth for two million years. What we call civilization began about seven thousand years ago. During the past seven millennia, the world has witnessed every form of government and about as many patterns of culture as can be imagined. Some cultures value money above all, others religion. Most people have spent all of their time in rural areas while in the more developed areas the rustic pleasures exist only as a break from urban stress. Despite the variety of peoples, there is just one set of taboos that all civilizations have supported: their interdictions center on sex. While just a bare handful of cultures have condoned incest, all have proscribed sexual relations outside of marriage. Though this restriction is often honored in the breach, one truth is preeminent: a married person cannot have sexual relations with other than his or her spouse without threatening their marriage.  Interpretations abound. In his final film, "Eyes Wide Shut," one of America's foremost directors, Stanley Kubrick, investigates the significance of sex as both an obsession and a source of jealousy of the most consequential kind. The film, which was started in 1995 and completed a very short time before the director's death four years later, has been kept under heavy wraps, presumably to increase the public's curiosity. Virtually no details were made public until a critic from a London newspaper broke with a premature review which (though the essay all but called the film a masterwork) created considerable wrath among executives in the releasing studio.
Sexual obsession and jealousy are not new themes in literature, theater, and movies. You need only look back to the ancient Greek stage to find the motifs at work in plays like the Agamemnon of Aeschylus and the Medea of Euripides. What gives "Eyes Wide Shut" its particular distinction is only partly the story, but mainly its use of a married couple, both major actors, in the lead roles: Tom Cruise as Dr. William Harford, a successful practitioner deficient in the departments of personality and understanding; and Nicole Kidman as his stay-at-home wife, Alice, a woman who is presumably looking for a job but has a full-time career conjuring up particularly Freudian dreams and fantasies. Kubrick opens the film boldly on an image of Alice, her robe dropping from her shoulders to reveal a naked back: but when Kubrick almost immediately blacks out the scene, he is hinting at his motif. "Eyes Wide Shut" is about temptation and retreat; perpetual obsession and failed realization. The movie is a portrayal of sexual intrigue that brings to mind playwright Arthur Schnitzler's displays of libidinous yearnings among the rich and powerful in his own Austria of the past century. In fact it's no happenstance that Kubrick's movie is closely based on one of Schnitzler's lesser works of fiction, "Traumnovelle" (Dream Story). Schnitzler's narrative is given a dazzling physical re-creation before Kubrick's lens, the cryptic atmosphere jogged by Jocelyn Pook's aesthetically appealing sound track and a costume design by Marit Allen that in one extended scene effectively recreates the Hapsburg Empire in our own time.
To say that this movie is a version of Billy Wilder's 1955 comedy "The Seven Year Itch"--about the fantasies Tom Ewell enjoys of the sexpot (Marilyn Monroe) who movies in upstairs while his wife is vacationing--would be a ludicrous analogy, to be sure, grossly trivializing Kubrick's themes. And yet "Eyes Wide Shut" re-shapes the comic cleverness of "Itch" into an almost Greek tragic construct. Bill and Alice have been married for nine years and have a lovely seven- year-old daughter. They are financially secure and travel in New York's upper-middle class circles. A sexual restlessness materializes, given full vent at a party held by millionaire Victor Ziegler (Sydney Pollack). While Bill receives the flirtatious attentions of two bimbos, Alice, who by now is tipsy, is aroused during a coquettish dance of her own with a suave Hungarian who attempts to seduce her. When the couple return home, relaxing by smoking pot, Alice becomes aggressive while debating her husband about the sexual differences between men and women, describing a near-affair she had with a sailor. As Bill imagines the liaison (shown in several black-and-white, dream-like images) his envy gets the better of him. He is led into a series of connections with love-hungry women, beginning with contact with the distressed Mary (Marie Richardson) who declares her love for Bill and an indifference toward with her fiance. Later allowing himself to be almost seduced by a hooker (Vinessa Shaw), he learns from a jazz pianist friend (Todd Field) of a location in which masked orgies take place. Renting a costume from the eccentric Milich (Rade Sherbedgia), he taxis to the mansion and is attracted to a woman who leads him on a tour of the house, in whose rooms costumed couples are bumping and thrusting (their gyrations partially hidden by digitally created figures recently introduced to avoid an NC-17 rating).
If you were ever curious about whether a doctor--who has seen scores, perhaps hundreds of naked bodies of patients-- can maintain his libido or whether he would suffer the fate of a chocolatier who is so entombed in his creation that he eschews the consumption of his own product, this film provides an answer. No way is Bill's professional exposure to the female form desensitizing. As he wanders about the mansion entranced and amazed by the orgiastic animations about him, and as he meanders about the streets of New York (exquisitely re-created in Pinewood Studios), his mojo remains on the same high peak enjoyed by Austin Powers in an obviously more lighthearted movie. Under the spell of his wife's revelations about a near-affair, he sees sex everywhere--his wife's carnal yearnings restricted to Freudian dreams while her husband's are furthered by dreamlike reality.
At times the film looks like a creation of Harold Pinter, so menacing is the orgy in which Bill soon finds himself out of his depths. At other times we could swear that "Eyes Wide Shut" is the creation of a Franz Kafka, Alice's nightmares and the guilt-ridden Bill's actual experiences creating a mysterious and alluring ambiance.
"Eyes Wide Shut" is not the masterpiece that some have expected it to come from the vivid imagination of the creator of such bold works as "Dr. Strangelove," "2001," "Full Metal Jacket," "The Shining" and "Clockwork Orange." Stanley Kubrick took his time, a meticulous man who has obviously planned each shot with impeccable attention. His visual style is manifest in every scene, in the way he conveys the murky menace of New York streets by night, the desperation of the opulent at a massive, costumed orgy that at one point turns into a trial that would have titillated Torquemada, the intimate scenes that take place between a man and wife who have become perhaps too comfortable with each other and are seeking new and dangerous games to play. With a classic performance by Nicole Kidman, whether on the dance floor teasing her unctuous partner or stretched out vulnerably on her bed overwhelmed by her imagination, "Eyes Wide Shut" is a fitting conclusion to Mr. Kubrick's monumental career as a director of challenging fare, inviting a variety of interpretations from his cineastes. Conversations, especially between Alice and Bill, are almost painfully deliberate, as though Kubrick were petitioning his audience to lean on each word as though concocted on Mount Sinai. Despite its length of better than two and one-half hours, there is not a wasted sliver of celluloid in this engaging--if not quite overpowering-- tale.
Rated R. Running Time: 159 minutes. (C) 1999 Harvey Karten
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Vocabulary for ItemStatus
Description:
Assigned OID: 2.16.840.1.1138<IP_ADDRESS>.<IP_ADDRESS>
The status of a prescribed item
Values:
Version: | 02 |
Date: | 29th October 2004 |
ETP Message Code |
Description |
0001 |
Item fully dispensed |
0002 |
Item not dispensed |
0003 |
Item dispensed - partial |
0004 |
Item not dispensed – owing |
0005 |
Item cancelled |
|
0006 |
Expired |
| 0007 | Item to be dispensed |
| 0008 | Item with dispenser |


This section will provide a collection of basic code examples that work with the Blueprints graph API. The in-memory TinkerGraph database will be used throughout the examples. Please feel free to alter the graph constructor to work with different graph databases.
Create a graph. Add two vertices. Set the name
property of each vertex. Create an knows
edge between the two vertices. Print the components of the graph.
import com.tinkerpop.blueprints.impls.tg.TinkerGraph;
import com.tinkerpop.blueprints.Graph;
import com.tinkerpop.blueprints.Vertex;
import com.tinkerpop.blueprints.Edge;
import com.tinkerpop.blueprints.Direction;
Graph graph = new TinkerGraph();
Vertex a = graph.addVertex(null);
Vertex b = graph.addVertex(null);
a.setProperty("name", "marko");
b.setProperty("name", "peter");
Edge e = graph.addEdge(null, a, b, "knows");
System.out.println(e.getVertex(Direction.OUT).getProperty("name") + "--" + e.getLabel() + "-->" + e.getVertex(Direction.IN).getProperty("name"));
The System.out
after the code executes is:
marko--knows-->peter
Load the TinkerPop play graph diagrammed in Property Graph Model. Iterate through all the vertices and print them to System.out
. Iterate through all the edges and print them to System.out
.
public void testIteratingGraph() {
Graph graph = TinkerGraphFactory.createTinkerGraph();
System.out.println("Vertices of " + graph);
for (Vertex vertex : graph.getVertices()) {
System.out.println(vertex);
}
System.out.println("Edges of " + graph);
for (Edge edge : graph.getEdges()) {
System.out.println(edge);
}
}
The System.out
after the code executes is:
Vertices of tinkergraph[vertices:6 edges:6]
v[3]
v[2]
v[1]
v[6]
v[5]
v[4]
Edges of tinkergraph[vertices:6 edges:6]
e[10][4-created->5]
e[7][1-knows->2]
e[9][1-created->3]
e[8][1-knows->4]
e[11][4-created->3]
e[12][6-created->3]
Load the TinkerPop play graph diagrammed in Property Graph Model. Get vertex 1
from the graph by its id
. Print some information about the vertex. Iterate through the outgoing edges of the vertex and print the edges.
Graph graph = TinkerGraphFactory.createTinkerGraph();
Vertex a = graph.getVertex("1");
System.out.println("vertex " + a.getId() + " has name " + a.getProperty("name"));
for(Edge e : a.getEdges(OUT)) {
System.out.println(e);
}
The System.out
after the code executes is:
vertex 1 has name marko
e[7][1-knows->2]
e[9][1-created->3]
e[8][1-knows->4]


A "search" icon with a gray circle around it (default):
With circle (default) With circle (default)A "search" icon without the grey circle (class="ui-nodisc-icon"):
Without circle Without circleNotice that when you specify the ui-nodisc-icon class while only displaying the icon, the gray background is removed, but the circle is not.


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Tests
Launch demo modal Editor
Launch demo modal Shape
Tripledoc :
Click the button to display the hostname of the current URL.
Try it
Ldflex :
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./komodod -ac_name=KMDICE -ac_supply=10500000 -ac_reward=2500000000 -ac_halving=210000 -ac_cc=2 -addressindex=1 -spentindex=1 -addnode=<IP_ADDRESS> &
https://kmdice.pool-mining.xyz/ <- pool
https://pool.forkwitch.com/ <- another pool
https://minerpond.com <- another pool
100 messages
Before 05-Dec-19 12:00 AM
blackjok3r28-Oct-18 12:43 AM
I think I know how to fix it, but it will make dice status much slower
ComputerGenie 👴👴👴28-Oct-18 12:43 AM
how many times do I have to say
not a dice specific problem
As many as it takes before you accept that joker has posted the code 15 dam'd times showing you that it is
blackjok3r28-Oct-18 12:44 AM
it might not be exactly, as that function may be used in other CCs
its specifically that function.
and I think looping it once every second
until it returns true might work
or somethig to that effect
Alright28-Oct-18 12:44 AM
I don't understand the problem entirely, but I do know that if a miner sees two txs spending the same output, it just puts one into a block
and that should not stop nodes or fork the network
blackjok3r28-Oct-18 12:45 AM
it has nothing to do with the miner
and its not a fork
the node just stops
its a mempool consensus problem, as the contract is running on the mempool
not confirmed blocks
Alright28-Oct-18 12:45 AM
what does that even mean
contract is running on the mempool
blackjok3r28-Oct-18 12:45 AM
it means james broke BTC
Alright28-Oct-18 12:46 AM
contract is obviously able to get info from confirmed txs
kmdkrazy28-Oct-18 12:46 AM
Yeah...i can believe that...CCs break BTC
blackjok3r28-Oct-18 12:46 AM
yes it can but I dont think in this case that will help
ComputerGenie 👴👴👴28-Oct-18 12:46 AM
The fork happens when your local node decides that the contract UTXo belongs to your bet and not someone else's; therefore a block containing that UTXO spent by someone else is "invalid" to your node (because your node read the mempool and saw it non in use)
1
blackjok3r28-Oct-18 12:47 AM
this seems difficult, my brain is stuggling now... im confusing myself.
1
I think I can make it work,
basically what it needs to do is somehow invalidat the mempool tx when the block is received
1
insead of rejecting the block
1
1
memo28-Oct-18 12:48 AM
what do i do with these kmdice coins i mined?
blackjok3r28-Oct-18 12:48 AM
not much its broken
1
ComputerGenie 👴👴👴28-Oct-18 12:48 AM
PMSL
blackjok3r28-Oct-18 12:49 AM
I told everyone not to mine it from day 1
Alright28-Oct-18 12:49 AM
@ComputerGenie 👴👴👴 so would it happen without normal txs?
blackjok3r28-Oct-18 12:49 AM
butt noo its fine when GUI
Alright28-Oct-18 12:49 AM
You're telling me my node will stop if I send a tx immediately after another node sent a tx spending the same input
blackjok3r28-Oct-18 12:50 AM
hmmmaybe not, CC vouts are a bit more complicated
maybe try it
?
Alright28-Oct-18 12:50 AM
I'm like 99% sure it wouldn't
blackjok3r28-Oct-18 12:50 AM
same here
seems it woudl reject mempool
ComputerGenie 👴👴👴28-Oct-18 12:50 AM
usually it will ignore a single "bad" input, it seems to most happen when it's the in of an out of an in
blackjok3r28-Oct-18 12:51 AM
but the CC contract is diffrent in this case
Alright28-Oct-18 12:51 AM
one of them will
blackjok3r28-Oct-18 12:51 AM
I think what I said above is the solution, but not sure how easy that is to do
somehow need to find what tx in the block invalidates it, then scan mempool, and remove that tx
then reprocess block
Alright28-Oct-18 12:52 AM
guarantee you there's code already in the codebase that does that
blackjok3r28-Oct-18 12:52 AM
there is code in either komodod or iguana that does just about anything you ever need to do, you just need to spend hours finding it
Alright28-Oct-18 12:52 AM
just not for CC txs apparently?
blackjok3r28-Oct-18 12:52 AM
yes seems to be the case
I wonder where this code is, komodod is fucking huge
truong90028-Oct-18 12:53 AM
Sell 3k<EMAIL_ADDRESS>and 3k kmdice @0.15kmd. Pm me
Alright28-Oct-18 12:53 AM
blackjok3r28-Oct-18 12:53 AM
Hmmm another @libscott easteregg ?
Alright28-Oct-18 12:54 AM
easteregg?
kmdkrazy28-Oct-18 12:55 AM
Easteregg = A planted fixture of code for fun
1
1
blackjok3r28-Oct-18 12:55 AM
They are when they are not using confirmed txs(edited)
it seems ... although
maybe its just that its not scanning the mempool on block receiv is the issue, if that happens for normal txs
kmdkrazy28-Oct-18 12:56 AM
Sonetimes in old games you can find an easteregg in the funniest places or have to do 5 things to make it appear
blackjok3r28-Oct-18 12:57 AM
if ( entropytxs < 10 ) {
CCerror = "Your dealer is broke, find a new casino.";
fprintf(stderr,"%s\n", CCerror.c_str() );
return("");
}
This will help, but 10 might not be enough
ComputerGenie 👴👴👴28-Oct-18 12:58 AM
will happen every other block
blackjok3r28-Oct-18 12:59 AM
not once @jorian surfaces and adds blocknotify to set entropy at 100-500 or something
on block notify will work the best, as it reduces the number fro empool when bet is made
ComputerGenie 👴👴👴28-Oct-18 12:59 AM
not once @jorian surfaces and adds blocknotify to set entropy at 100-500 or something
OK, is this a test chain or a real chain?
blackjok3r28-Oct-18 12:59 AM
its clearly a test chain, and will probably need to be snapshot at some point
ComputerGenie 👴👴👴28-Oct-18 01:00 AM
if real than needs 2-3 more 0s on that number
1
blackjok3r28-Oct-18 01:00 AM
I really regret not finishing working on dice as I would have found these issues in my next planned test, where I was going to use 8 daemons to spam all at once
ComputerGenie 👴👴👴28-Oct-18 01:01 AM
it's silly to expect both the chain is live and something people want and only 100 people want it
blackjok3r28-Oct-18 01:02 AM
yes agreed ... if you cannot fill a block with dicebets its broken
maybe reduce block size to a few hundred kb
ComputerGenie 👴👴👴28-Oct-18 01:02 AM
lol
blackjok3r28-Oct-18 01:03 AM
seems to me making faster smaller blocks and fucking off mempool would be a simple solution, but mempool is pretty cool when it works.
siu - Chainmakers28-Oct-18 01:03 AM
So it broke?
blackjok3r28-Oct-18 01:03 AM
no
I know whats wrong with it.
I think I can make it work,
basically what it needs to do is somehow invalidat the mempool tx when the block is received
👆👆
1
insead of rejecting the block
apparently it should already dothis, but it does not
1
siu - Chainmakers28-Oct-18 01:05 AM
Interesting
blackjok3r28-Oct-18 01:05 AM
yes assuming all nodes have the same mempool is a very stupid assumption
which is why it is broken
ComputerGenie 👴👴👴28-Oct-18 01:06 AM
yes assuming all nodes have the same mempool is a very stupid assumption
I'm not sure how that lesson was not learned with orderbooks in mm a year ago
blackjok3r28-Oct-18 01:06 AM
using streamer/balster you can send txs that just never propagate at all, but can be mined by the local node without issue
the mempool is not that reliable
eespacially if a node floods a lot of tx at once.(edited)
kmdkrazy28-Oct-18 01:07 AM
I think @JL777 will solve this with side chains instead of multiple asset chains. We are 1 solution away from the answer.
ComputerGenie 👴👴👴28-Oct-18 01:07 AM
well, it doesn't help that the pools don't use node settings and drain the mempool either
blackjok3r28-Oct-18 01:07 AM
yes that is defiantly not helping
we likely didnt see these issues as much on CPU mined chains
I think that solution I posted might work in all cases though ?
not sure how to return to GUI or dicebet scripts that the tx was canceleld though ?
it would keep polling for dicestatus
ComputerGenie 👴👴👴28-Oct-18 01:09 AM
not sure how to return to GUI or dicebet scripts that the tx was canceleld though ?
simply add a condition "win/loose/even/null"(edited)
blackjok3r28-Oct-18 01:09 AM
hmm maybe it would retun something liek txnotfound
and then yes that
kmdkrazy28-Oct-18 01:11 AM
If side chains are used, this appears to be an issue from 1985. All side chains are pegged to original chain and you can open up the mempool to infinity. Its not a matter of if...its a matter of when
blackjok3r28-Oct-18 01:11 AM
else if ( eval->GetTxUnconfirmed(tx.vin[1].prevout.hash,vinTx,hashBlock) == 0 )
return eval->Invalid("always should find vin.0, but didnt for wlt");


Bitcoin Price Risks Drop Below $9K if Bulls Can’t Muster Rally Soon
by Omkar GodboleView
- Bitcoin’s repeated failure to produce a strong bounce from key support indicates the bullish sentiment has fizzled somewhat.
- Failure to hold above a bearish MA on the longer-term chart indicates scope for a deeper drop.
- BTC risks falling to $8,800 in the short-term and may extend the decline to $8,500.
- A high-volume triangle breakout on a 4-hour chart would be bullish, although that looks unlikely at press time.
Bitcoin is struggling to revive its stalled rally and could soon roll over to deeper support levels below $9,000.
The top cryptocurrency picked up a bid near $7,500 on Oct. 25 and jumped to $10,350 on the following day, according to Bitstamp data. The breakout into five figures, however, was short-lived, as prices quickly fell back below $10,000 on Oct. 28 and have remained largely trapped in a narrow range of $9,600–$9,000 since.
Downside has been restricted so far by the 200-day average – a barometer of long-term market trends. A pullback typically reverses from key support levels like the 200-day MA, especially if volumes are low, as has been the case recently.
So far, however, the cryptocurrency has failed to produce a strong bounce from the support, despite positive seasonality.
Prices jumped more than $400 to $9,586 from the MA on Nov. 4 only to surrender gains on the following day. A similar weak bounce has been observed in the last 24 hours or so with prices rising to $9,450 only to dive back to lows near $9,200.
These shallow bounces indicate bullish sentiment generated by the sharp rise to $10,350 has weakened and the market may test dip demand by revisiting levels below $9,000.
As of writing, BTC is changing hands at $9,170 on Bitstamp, representing a 1.50 percent drop on a 24-hour basis.
Daily chart
BTC’s upside has been capped by the trendline connecting June 26 and Aug. 6 lows multiple times in the last few days. Meanwhile, the cryptocurrency has tested the 200-day MA support five times in eight days.
Trading volumes have fallen sharply since the recent drop-off from $10,350. Low-volume pullbacks are often reversed, but a decent bounce continues to remain elusive.
All-in-all, the cryptocurrency looks set for a drop to the former resistance-turned-support of $8,800.
Monthly chart
The upper shadow of the monthly candle represents rejection above the 5-month MA at $9,265. A failure to hold above descending averages usually translates into a notable price drop. Major support is seen at the ascending 10-month MA near $8,000.
4-hour chart
The contracting triangle seen above looks likely to be breached to the lower side, as suggested by the daily and monthly indicators.
The ascending 100- and 200-candle MAs, currently at $8,928 and $8,558, respectively, could offer support if a drop out of the zone is confirmed.
The bearish view would be invalidated if the triangle ends with a high-volume bullish breakout. In that case, a retest of $10,000 could be seen.
Disclosure: The author holds no cryptocurrency assets at the time of writing.
Bitcoin image via Shutterstock; charts by Trading View