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This actually helped me the best as my date difference was half a day but still when America is 1 day behind Australia I need to see there's actually one day difference. The other answers mentioned in this thread was showing either zero or some double number below 1 which I don't need.
This is the best answer when the purpose is to check if the date has already passed to the next day, no matter if in terms of time is not a full 24h day. ReadKey ;. Vijay Vj Vijay Vj 3 3 silver badges 14 14 bronze badges. AddDays ; string cc; Console. WriteLine d ; Console. Days; Console. ReadLine ;. Pratyush Dhanuka Pratyush Dhanuka 1, 1 1 gold badge 10 10 silver badges 20 20 bronze badges. ToInt32 DateTime. Date - myDateTime.
TotalDays ; This calculates the total days from today DateTime. Happy coding! Curbside Coder Curbside Coder 3 3 silver badges 15 15 bronze badges. Couldn't you just use "Days" instead of casting TotalDays? That conversion doesn't even round, it just truncates. Parse txtstartdate. Parse txtenddate. Here is an example:. Muba Muba 17 1 1 bronze badge. Subtract StartDate. Muhamad Eissa Muhamad Eissa 61 5 5 bronze badges. While this code snippet may solve the question, including an explanation really helps to improve the quality of your post.
Remember that you are answering the question for readers in the future, and those people might not know the reasons for your code suggestion.
Please also try not to crowd your code with explanatory comments, as this reduces the readability of both the code and the explanations! TotalDays returns a double: msdn. ToInt32 d1[2] , Convert. ToInt32 d1[1] , Convert. ToInt32 d2[2] , Convert. ToInt32 d2[1] , Convert. ToString ;. Things should run the same as before except that we are one step closer to modularizing the project!
Named modules are all about defining the surface area of your API. Now that we have a tool which allows us to hide implementation details that would otherwise be unnecessary for consumers, we can start to think about what the accessible parts of the API should be.
In this file we have the following declarations:. As such we can define the module like so:. Notice that we do not even need to export the declaration of the class RandomNumberGenerator. Do not be afraid to put compiled code in an interface, it is its own translation unit and obeys the rules of compiled code.
When we move code into a modules world, and in particular 3rd party code, we need to take some things into consideration: what part of the library do we want to expose? What runtime requirements are in the library if it is header only? With modules we start to have answers to these questions based on the requirements of our project.
Integrating 3rd party library functionality into modularized projects is one of the most interesting parts of using modules because modules give us tools we never had before to deal with ODR One Definition Rule and name resolution. It is easy to integrate into projects because it is a single header file and the interfaces are simple—which plays to our advantage in deciding what parts of the library we want to expose.
You will immediately notice that the color constants are mysteriously missing. This is because these constants are defined with static linkage in the header file so we cannot export them directly and the reason is buried in standardese. It is simpler to remember that you cannot export an internal linkage entity i.
The way to get around this is wrap them in a function which has module linkage:. Once we have these functions, we need to replace any instance of olc::COLOR with its respective call to our exported color function. And that is it! Just as before, you add this to the CMakeLists. Once you have gone through the exercise of modularizing more and more of the project you might find that your main program begins to reflect the header file version:.
To understand what I am talking about let us look at a header file equivalent of grouping common functionality. The problem, of course, is while this is convenient and you do not need to think about which specific file to include for your current project, you end up paying the cost of every header file in the package regardless of if you use it or not. We can also do the same for anything under Util.
This leads us to a rather, I think, respectable looking ball-pit. It was a little bit of a journey getting here, and there are learnings along the way.
You can check out the code, configure, and build it the same as we covered earlier using Visual Studio version With modules there is an up-front cost in building our interfaces. With the old inclusion model, we did not have to build our include files explicitly only implicitly. We end up building more up front, but the result is that we can REPL our main program and its components much, much faster. Here is a snapshot of the difference:.
As a result of this, it is typically the case that many of the higher frequency components are rounded to zero, and many of the rest become small positive or negative numbers, which take many fewer bits to represent. The elements in the quantization matrix control the compression ratio, with larger values producing greater compression. Notice that most of the higher-frequency elements of the sub-block i. Entropy coding is a special form of lossless data compression.
It involves arranging the image components in a " zigzag " order employing run-length encoding RLE algorithm that groups similar frequencies together, inserting length coding zeros, and then using Huffman coding on what is left. The JPEG standard also allows, but does not require, decoders to support the use of arithmetic coding , which is mathematically superior to Huffman coding. However, this feature has rarely been used, as it was historically covered by patents requiring royalty-bearing licenses, and because it is slower to encode and decode compared to Huffman coding.
The previous quantized DC coefficient is used to predict the current quantized DC coefficient. The difference between the two is encoded rather than the actual value. The encoding of the 63 quantized AC coefficients does not use such prediction differencing. The zigzag sequence for the above quantized coefficients are shown below. This encoding mode is called baseline sequential encoding. Baseline JPEG also supports progressive encoding. While sequential encoding encodes coefficients of a single block at a time in a zigzag manner , progressive encoding encodes similar-positioned batch of coefficients of all blocks in one go called a scan , followed by the next batch of coefficients of all blocks, and so on.
Once all similar-positioned coefficients have been encoded, the next position to be encoded is the one occurring next in the zigzag traversal as indicated in the figure above. It has been found that baseline progressive JPEG encoding usually gives better compression as compared to baseline sequential JPEG due to the ability to use different Huffman tables see below tailored for different frequencies on each "scan" or "pass" which includes similar-positioned coefficients , though the difference is not too large.
In the rest of the article, it is assumed that the coefficient pattern generated is due to sequential mode. The JPEG standard provides general-purpose Huffman tables; encoders may also choose to generate Huffman tables optimized for the actual frequency distributions in images being encoded.
The process of encoding the zig-zag quantized data begins with a run-length encoding explained below, where:. The run-length encoding works by examining each non-zero AC coefficient x and determining how many zeroes came before the previous AC coefficient. With this information, two symbols are created:. The higher bits deal with the number of zeroes, while the lower bits denote the number of bits necessary to encode the value of x. This has the immediate implication of Symbol 1 being only able store information regarding the first 15 zeroes preceding the non-zero AC coefficient.
One is for ending the sequence prematurely when the remaining coefficients are zero called "End-of-Block" or "EOB" , and another when the run of zeroes goes beyond 15 before reaching a non-zero AC coefficient. In such a case where 16 zeroes are encountered before a given non-zero AC coefficient, Symbol 1 is encoded "specially" as: 15, 0 0.
The overall process continues until "EOB" — denoted by 0, 0 — is reached. See above. From here, frequency calculations are made based on occurrences of the coefficients. In our example block, most of the quantized coefficients are small numbers that are not preceded immediately by a zero coefficient. These more-frequent cases will be represented by shorter code words.
The resulting compression ratio can be varied according to need by being more or less aggressive in the divisors used in the quantization phase. Ten to one compression usually results in an image that cannot be distinguished by eye from the original. A compression ratio of is usually possible, but will look distinctly artifacted compared to the original.
The appropriate level of compression depends on the use to which the image will be put. Those who use the World Wide Web may be familiar with the irregularities known as compression artifacts that appear in JPEG images, which may take the form of noise around contrasting edges especially curves and corners , or "blocky" images. These are due to the quantization step of the JPEG algorithm. They are especially noticeable around sharp corners between contrasting colors text is a good example, as it contains many such corners.
The analogous artifacts in MPEG video are referred to as mosquito noise , as the resulting "edge busyness" and spurious dots, which change over time, resemble mosquitoes swarming around the object. These artifacts can be reduced by choosing a lower level of compression ; they may be completely avoided by saving an image using a lossless file format, though this will result in a larger file size.
The images created with ray-tracing programs have noticeable blocky shapes on the terrain. Certain low-intensity compression artifacts might be acceptable when simply viewing the images, but can be emphasized if the image is subsequently processed, usually resulting in unacceptable quality. Consider the example below, demonstrating the effect of lossy compression on an edge detection processing step.
Some programs allow the user to vary the amount by which individual blocks are compressed. Stronger compression is applied to areas of the image that show fewer artifacts. This way it is possible to manually reduce JPEG file size with less loss of quality. Since the quantization stage always results in a loss of information, JPEG standard is always a lossy compression codec. Information is lost both in quantizing and rounding of the floating-point numbers.
Even if the quantization matrix is a matrix of ones , information will still be lost in the rounding step. Rounding the output to integer values since the original had integer values results in an image with values still shifted down by This is the decompressed subimage. If this occurs, the decoder needs to clip the output values so as to keep them within that range to prevent overflow when storing the decompressed image with the original bit depth.
The error is most noticeable in the bottom-left corner where the bottom-left pixel becomes darker than the pixel to its immediate right. These requirements are specified in ITU.
T Recommendation T. For example, the output of a decoder implementation must not exceed an error of one quantization unit in the DCT domain when applied to the reference testing codestreams provided as part of the above standard. While unusual, and unlike many other and more modern standards, ITU. JPEG compression artifacts blend well into photographs with detailed non-uniform textures, allowing higher compression ratios. Notice how a higher compression ratio first affects the high-frequency textures in the upper-left corner of the image, and how the contrasting lines become more fuzzy.
The very high compression ratio severely affects the quality of the image, although the overall colors and image form are still recognizable. However, the precision of colors suffer less for a human eye than the precision of contours based on luminance. This justifies the fact that images should be first transformed in a color model separating the luminance from the chromatic information, before subsampling the chromatic planes which may also use lower quality quantization in order to preserve the precision of the luminance plane with more information bits.
For information, the uncompressed bit RGB bitmap image below 73, pixels would require , bytes excluding all other information headers. The filesizes indicated below include the internal JPEG information headers and some metadata. On grayscale images, a minimum of 6. For most applications, the quality factor should not go below 0. The image at lowest quality uses only 0. This is useful when the image will be displayed in a significantly scaled-down size.
The medium quality photo uses only 4. However, once a certain threshold of compression is passed, compressed images show increasingly visible defects. See the article on rate—distortion theory for a mathematical explanation of this threshold effect. More modern designs such as JPEG and JPEG XR exhibit a more graceful degradation of quality as the bit usage decreases — by using transforms with a larger spatial extent for the lower frequency coefficients and by using overlapping transform basis functions.
From to , new research emerged on ways to further compress the data contained in JPEG images without modifying the represented image. Standard general-purpose compression tools cannot significantly compress JPEG files.
Typically, such schemes take advantage of improvements to the naive scheme for coding DCT coefficients, which fails to take into account:. Some standard but rarely used options already exist in JPEG to improve the efficiency of coding DCT coefficients: the arithmetic coding option, and the progressive coding option which produces lower bitrates because values for each coefficient are coded independently, and each coefficient has a significantly different distribution.
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Details required :. Cancel Submit. How satisfied are you with this comment? In reply to RaymondHuang's post on July 3, You can download the installation file for OneNote desktop software from Install or reinstall OneNote for Windows If you have 32 bit Office installed, you need to use the bit Onenote installer.
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