Commonly used image tokenizers produce a 2D grid of spatially arranged tokens. In contrast, so-called 1D image tokenizers represent images as highly compressed one-dimensional sequences of as few as …

[Ebony Berger]

Commonly used image tokenizers produce a 2D grid of spatially arranged tokens. In contrast, so-called 1D image tokenizers represent images as highly compressed one-dimensional sequences of as few as 32 discrete tokens. We find that the high degree of compression achieved by a 1D tokenizer with vector quantization enables image editing and generative capabilities through heuristic manipulation of tokens, demonstrating that even very crude manipulations -- such as copying and replacing tokens between latent representations of images -- enable fine-grained image editing by transferring appearance and semantic attributes. Motivated by the expressivity of the 1D tokenizer's latent space, we construct an image generation pipeline leveraging gradient-based test-time optimization of tokens with plug-and-play loss functions such as reconstruction or CLIP similarity. Our approach is demonstrated for inpainting and text-guided image editing use cases, and can generate diverse and realistic samples without requiring training of any generative model.
Generating realistic images with AI is difficult because images contain hundreds of thousands of pixels with complex relationships. To make this easier, the image generation task is typically split into two steps: first "compress" the image into a smaller set of meaningful pieces called "tokens," then learn how these tokens relate to each other.Recent advances have created extremely efficient compression methods that can represent an entire image using just 32 small integers. We discovered that these compressed representations actually capture surprisingly rich information about what's in the image that humans can understand.More importantly, we found that you can edit images by simply manipulating these 32 tokens directly -- no complex AI training required. Furthermore, we show that this enables users to define any custom goal or "objective function" for how they want their image to look, and our system can achieve it in just a few seconds without needing to train new models. Our examples demonstrate this approach for various image tasks like text-guided editing, filling in missing parts, and generating new images from text descriptions.
Scientists of the "SPring-8 Joint Project for XFEL" (Nobuo Fujishima, Director), a joint project of RIKEN (Ryoji Noyori, President) and Japan Synchrotron Radiation Research Institute (JASRI; Tetsuhisa Shirakawa, President), have developed a method of efficiently compressing a high-quality electron beam to achieve a few-thousand-times higher density and have clarified its effectiveness by computational simulation.*1 This method will greatly contribute to improving the optical performance and stability of the X-ray free electron laser (XFEL).*2
XFEL is a new light source with excellent characteristics of angstrom-level*3 spatial resolution and femtosecond-level*4 time resolution that will be used for irradiating substances. Scientists worldwide as well as industry have high expectations that the XFEL will trigger innovations in life science and nanotechnology, for example, the development of effective drugs for intractable diseases including cancer and AIDS and breakthroughs in research on new energy systems necessary for the sustainable development of our society.
These achievements will lead to a dramatic improvement in the light performance and stability of the world's smallest XFEL facility (Fig. 1), now under construction on the campus of SPring-8 (Harima Science Garden City) as the joint project by RIKEN and JASRI whose target completion date is in FY 2010, and will pave the way for the further downsizing of the XFEL system in the future.
Fig. 1XFEL facility under construction on the campus of SPring-8 A compact, slendar XFEL facility is being constructed, as shown in the top left of the photograph. Electrons are accelerated from left to right. Five beamlines will be installed in the experimental facility (under construction further downstream). The circular facility to the right of the XFEL facility is the SPring-8 storage ring and the surrounding experimental hall. Currently, 50 beamlines are operational in these facilities, which have circumference of about 1.5 km.
Fig. 2Tunnel interior of SCSS test accelerator A high-voltage tank of the electron gun is shown in the foreground. An electron beam is emitted from the hot cathode behind the tank towards two undulators downstream.
Fig. 3Schematic of bunch compression by electromagnet chicane Red, black, and light-blue circles represent the top, center, and tail of an electron bunch, respectively. The three circles indicate how an electron bunch with gradually increasing energy from the top to the tail is compressed while passing through the chicane.
Fig. 4Principle of linearization of energy chirp (conventional method)The figure shows the accelerating electric field (red dotted line), the decelerating electric field with a frequency threefold higher than that of the accelerating electric field (blue dotted line), and the electric field obtained by superposing them (black dotted line). The superposed electric field becomes partly linear.
Fig. 5Curve of energy chirp enhanced by compression Compressing the electron beam sharpens the curve of the energy chirp. The threefold-compressed electron beam acts similarly to the third harmonic electric field without changing frequency.
Fig. 7Enhanced correction effect of first-stage bunch compressor When the compression coefficient is 6 or smaller, the voltage used for correcting the curve decreases quadratically with increasing compression coefficient. When it is greater than 6, the effect of the compressor gradually decreases and the correction voltage approaches a constant value.
*1Computational simulation The program used for integrating the motion of the electron beam in three-dimensional electromagnetic fields, where the three-dimensional space-charge effect, coherent synchrotron radiation, and spontaneous emission are taken into consideration.
*2X-ray free electron laser (XFEL) World's state-of-the-art research facility that will produce X-rays at least one billion times brighter than current synchrotron radiation and will enable the analysis of atomic-level ultrafine structures and the instantaneous measurement of ultrahigh-speed dynamics and structural changes in chemical reactions. The XFEL was designated a key technology of national importance in the 3rd Science and Technology Basic Plan of Japan, and has been under construction next to SPring-8 in Harima Science Garden City, since FY 2007. The public use of the XFEL facility is planned to start in FY 2011. The XFEL has the aim of opening up new research areas in various fields of science and technology, such as life science, nanotechnology, and materials science, and of achieving breakthroughs ahead of Europe and the US.
*5SCSS test accelerator and self-amplified spontaneous emission SCSS is an abbreviation for the SPring-8 Compact SASE Source, where SASE stands for self-amplified spontaneous emission. The SCSS test accelerator is an extreme ultraviolet free electron laser generator operating on the principle of SASE.
The Pepsi bottling plant in Winnipeg, Manitoba has upgraded both their main 100 psi compressed air system and their 600 psi PET bottling system in two separate projects. The system improvements have saved the company both maintenance and electrical operating costs, and even reduced some winter heating demand.
The first project started, a number of years ago, when the 100 psi compressed air system needed replacing due to the advanced age of the air compressors. The previous units were 100 hp fixed speed units operating in a combination of modulation and load unload mode. The system used standard compressed air filters and non-cycling air dryers. During normal operation, the plant pressure ranged from a high of 107 psi to as low as 78 psi due to pressure differentials in the system. The plant had already implemented some improvements to their system in eliminating compressed air drying on their filling lines, and by turning off the main compressors on weekends (a small reciprocating compressor was used). Plant personnel were interested in renewing the compressed air system to make it more efficient, and had heard of the power utility incentives offered, so they requested some energy analysis.
Data loggers were placed on the 100 psi system, which showed the compressed air system was running inefficiently due to the type of air compressor control and the lack of enough storage receiver capacity. The system also had some significant pressure differentials across the piping, air dryer, and filtration system. Leakage was estimated at 27 percent of the average flow and the timer style condensate drains were contributing to wasted flow. Estimated energy consumption was pegged at 746,000 kWh per year, about 11 percent of the total facility electrical costs. The utility predicted that if a VSD compressor was installed, along with other improvements, an operating cost saving of 35 percent could be gained.
Further to this, some preliminary assessment of the 600 psi PET bottle blowing system was done. This system used a 600 hp multi-stage water-cooled reciprocating compressor to supply the system that produced plastic beverage bottles, first passing the air through a refrigerated air dryer. This system was identified as an item that contributed significantly to the plant energy costs, mainly through peak demand charges. No work was done initially, but further testing a few years later found that this system, and an associated evaporative cooling system consumed 1,425,000 kWh and contributed to a peak facility electrical demand of 425 kVa.
For the 100 psi system the local power utility, Manitoba Hydro, was able to help calculate the savings that could be gained through various upgrade options. Each option came with a corresponding possible incentive grant, this was used by the plant maintenance manager to help decide on the type of air compressor to purchase and the energy efficiency options to buy. This was done based on the CAGI data sheet data of the compressors being considered, and estimated pressure and power reductions. Calculation was done on a spreadsheet, which was developed by Manitoba Hydro. The following energy efficiency measures were selected: cc7c31b456

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Have you ever wanted a way to work out what shadow and lit colours you are supposed to use in your painting?Colour Constructor is a study and workflow tool that is designed to help you design the colours and values for a painting or image you are making according to a light source and ambient term.
I've started working on colour constuctor again full time. Rewriting the whole thing from scratch in a new engine, Should hopefully mean less bugs, better performance, 3d, and it will also let me rethink how everything works, and implement a bunch of features i wanted to do from the start but couldn't because of the limitations of the last engine.
New stuff i will be doing! *3d previews with changable lights and materials. (SSS!? metals?) *scene management, have folders to be able to organize all your colours. *colour pick from images
Stuff i want to do: *colour gamut generator. *Painting mode. I really want to implement a mode where you can paint flat materials and then handpaint a light/shadow map. This is going to take a lot of thought, but the idea seems like it could be very useful in design iterations, and could almost even be worked into a painting workflow that uses CC as your first colour pass, and export it to useable layers. This will take a lot of work and wont arrive for quite a while though.
This method applies an arbitrary scale factor to each of the three RGB components of this Color to create a brighter version of this Color. The alpha value is preserved. Although brighter and darker are inverse operations, the results of a series of invocations of these two methods might be inconsistent because of rounding errors.
This method applies an arbitrary scale factor to each of the three RGB components of this Color to create a darker version of this Color. The alpha value is preserved. Although brighter and darker are inverse operations, the results of a series of invocations of these two methods might be inconsistent because of rounding errors.
The saturation and brightness components should be floating-point values between zero and one (numbers in the range 0.0-1.0). The hue component can be any floating-point number. The floor of this number is subtracted from it to create a fraction between 0 and 1. This fractional number is then multiplied by 360 to produce the hue angle in the HSB color model.
The integer that is returned by HSBtoRGB encodes the value of a color in bits 0-23 of an integer value that is the same format used by the method getRGB. This integer can be supplied as an argument to the Color constructor that takes a single integer argument.
The s and b components should be floating-point values between zero and one (numbers in the range 0.0-1.0). The h component can be any floating-point number. The floor of this number is subtracted from it to create a fraction between 0 and 1. This fractional number is then multiplied by 360 to produce the hue angle in the HSB color model.
I am creating a project using Adafruit neopixels. I have tested the hardware using a simple program and that isnt the issue. Using the library is fine, but what I wanted to do is make a wrapper class which acts as an adapter since I want to think about my neopixels as a grid and set them using x,y coordinates, but the way they are wired makes this not a straight forward procedure. I also like the ability to make common place functions like setting a whole row or column the same colour.
My current setup is a main.ino file, a custom colour class (.cpp and .h) and an LEDController class (.cpp and .h). All the other code seems to be working fine, I have interrupts set up and can print stuff to verify this, but any calls to my wrapper object are not reflected on the physical led strip. The class holds a 2D array buffer (which I intend to use to do nice slow fades and the like) and I can dump this to the serial and see that the buffer has been updated. Its just sending this data to the neo pixel strip that doesnt seem to be working. For completeness I will attempt to include all my code unless theres some sort of limit i dont know about yet. Any help would be greatly appreciated.
Theres an interesting thing in the LEDController constructor. I initialise the strip variable which uses the adafruit library. I make sure to call strip.begin. However if I also try to call strip.clear and strip.show to ensure all LEDs are off at the start (as I understand good practice) then it seems to get stuck because my setup function in main.ino never prints the "done" message. I was also previously using pointers and got a situation where somehow setup was being re-called because I got the done message every few seconds. That was weird.
Yeah but theyre not wired the simple way. I agree that would be much easier, but the LEDs are actually wired in a snake sort of pattern. If you look at the comment in LEDController::getPixelIndex you can sort of see why its like that. Ive tested this function in isolation and it produces the correct result for my specific circuit. So the problem lies somewhere else.
That is called a serpentine raster. There are four ways to wire this up and the exact solution depends on which way it is wired. Basically on some lines the formula is like xfpd gave you but on other it is a different calculation.
I will look into this guide and the modules mentioned. It seems like maybe I can use those. I still personally wouldve liked a wrapper class but I guess I can implement fades and animations as stand alone functions.
However. To all the other replies, I can not stress this enough: The problem is not how I index the pixels. If you will scroll to the bottom of the included LEDController.cpp file, you will see that I have already derived those formulas myself (yes maybe a bit more research I wouldve found out its propper name and another library to do it for me) but this is not the issue. I have verified that function in isolation and all of the x y coordinates I pass in give me the correct index in relation to the wiring of the pixels. The issue is that in LEDController.push() the contents of ColourBuffer are not being reflected onto the physical LED strip
I suppose yes I could use the NeoMatrix module, or indeed move my own indexing function into main and store a 2d array as a global variable and make all my functions in main and make it a really messy file. My question is more why when I refactor it into its own wrapper function does it seem to no longer work, when to my eye at least, I cant spot any obvious code mistakes
The LED strips do not light up at all. The colourBuffer stores the correct values but calling push() causes no LEDs to turn on.I do not need to pass a pointer because i am reading from the class attribute directly, and then calling the setPixelColor function which is aprt of the adafruit library
Its worth mentioning at this point that thanks to @PaulRB's suggestion I have done more research and found that not only had this problem been solved before, its then been solved again by the FastLED library. This can literally do everything I wanted my class to do and more, and I will be using that for my project moving forwad.
Yes this post was originally about fixing my library. And a fair enough fix is finding a library that has been made far better by people before me. That being said I do not wish to abandon this thread as I still think I can learn what was wrong, and understand the neopixels more as a result
I have done more research and found that not only had this problem been solved before, its then been solved again by the FastLED library. This can literally do everything I wanted my class to do and more, and I will be using that for my project moving forwad.
The colour that is returned will be the targetColour, but with its luminosity nudged up or down so that it differs from the luminosity of this colour by at least the amount specified by minLuminosityDiff.
Java 8 gave us default methods on interfaces. These allowed us to mix together behaviour defined in multiple interfaces. One use of this is to avoid having to re-implement all of a large interface if you just want to add a new method to an existing type. For example, adding a .map(f) method to List. I called this the Forwarding Interface pattern.
How can we implement this in a way that requires minimal boilerplate? Default methods on interfaces come to the rescue again. What if we could get any of this additional sugary goodness on any record, simply by implementing an interface.
We want the Colour constructor. We can get it from Colour.class. We can get this by reflectively accessing the first type parameter of the TriTuple interface. Using Class::getGenericInterfaces() then ParameterizedType::getActualTypeArguments() and taking the first to get a Class
For example I am currently working on a large table (RACI chart). The bulk of the cells will be filled with a single letter, R, A, C or I. I'd like to colour code the cells for easier identification, let's say all R = Red, A = Yellow, C = Green and I = Blue. If I set up cell styles is there an easy way of automating this or do I have to go through and change each cell individually?
The easiest thing to do is write yourself a wrapper method that converts color names that SketchUp does not know into color names it does know before calling the Sketchup::Color constructor method.
But the discussion on materials is necessary, because the Sketchup::Color class when used in a SketchUp model, is only a property of a Sketchup::Material, so you will need to add a material for each SVG color as you import and paint the geometry. See the snippet above.
[color]=myvar, i have used like and in theme i have give color code, but the problem how i can change header color dynamically as per the condition, because in header bar i am not able to do the style or any class.
you need to use some ts file as provider for all of your preject.you put the var there as public.and in navbar you do(after putting it in the app constructor if im not mastaking):[color]=myVars.navColorthen in every page you want you define the provider in your constructor like:constructor(public myVars: MYVARS){