According to the Bluetooth Advertisement sample, I need to set the CompanyID (UInt16) and the Data (IBuffer, a UInt16 in the sample) to start watching for advertisers.
In the iPhone, I can set the beacon UUID to 4B503F1B-C09C-4AEE-972F-750E9D346784. And reading on the internet, I found Apple's company id is 0x004C, so I tried 0x004C and 0x4C00.
So, this is the code I have so far, but of course, it is not working.
var manufacturerData = new BluetoothLEManufacturerData();
// Then, set the company ID for the manufacturer data. Here we picked an unused value: 0xFFFE
manufacturerData.CompanyId = 0x4C00;
// Finally set the data payload within the manufacturer-specific section
// Here, use a 16-bit UUID: 0x1234 -> {0x34, 0x12} (little-endian)
var writer = new DataWriter();
writer.WriteGuid(Guid.Parse("4B503F1B-C09C-4AEE-972F-750E9D346784"));
// Make sure that the buffer length can fit within an advertisement payload. Otherwise you will get an exception.
manufacturerData.Data = writer.DetachBuffer();
I also tried inverting the bytes in the UUID:
writer.WriteGuid(Guid.Parse("504B1B3F-9CC0-EE4A-2F97-0E75349D8467"));
Not success so far. Am I mixing two completely different technologies?
The most important thing you need to do to detect Beacons on Windows 10 is to use the new BluetoothLeAdvertisementWatcher class.
The code in the question seems focussed on setting up a filter to look for only specific Bluetooth LE advertisements matching a company code and perhaps a UUID contained in the advertisement. While this is one approach, it isn't strictly necessary -- you can simply look for all Bluetooth LE advertisements, then decode them to see if they are beacon advertisements.
I've pasted some code below that shows what I think you want to do. Major caveat: I have not tested this code myself, as I don't have a Windows 10 development environment. If you try it yourself and make corrections, please let me know and I will update my answer.
private BluetoothLEAdvertisementWatcher bluetoothLEAdvertisementWatcher;
public LookForBeacons() {
bluetoothLEAdvertisementWatcher = new BluetoothLEAdvertisementWatcher();
bluetoothLEAdvertisementWatcher.Received += OnAdvertisementReceived;
bluetoothLEAdvertisementWatcher.Start();
}
private async void OnAdvertisementReceived(BluetoothLEAdvertisementWatcher watcher, BluetoothLEAdvertisementReceivedEventArgs eventArgs) {
var manufacturerSections = eventArgs.Advertisement.ManufacturerData;
if (manufacturerSections.Count > 0) {
var manufacturerData = manufacturerSections[0];
var data = new byte[manufacturerData.Data.Length];
using (var reader = DataReader.FromBuffer(manufacturerData.Data)) {
reader.ReadBytes(data);
// If we arrive here we have detected a Bluetooth LE advertisement
// Add code here to decode the the bytes in data and read the beacon identifiers
}
}
}
The next obvious question is how do you decode the bytes of the advertisement? It's pretty easy to search the web and find out the byte sequence of various beacon types, even proprietary ones. For the sake of keeping this answer brief and out of the intellectual property thicket, I'll simply describe how to decode the bytes of an open-source AltBeacon advertisement:
18 01 be ac 2f 23 44 54 cf 6d 4a 0f ad f2 f4 91 1b a9 ff a6 00 01 00 02 c5 00
This is decoded as:
The first two bytes are the company code (0x0118 = Radius Networks)
The next two bytes are the beacon type code (0xacbe = AltBeacon)
The next 16 bytes are the first identifier 2F234454-CF6D-4A0F-ADF2-F4911BA9FFA6
The next 2 bytes are the second identifier 0x0001
The next 2 bytes are the third identifier 0x0002
The following byte is the power calibration value 0xC5 -> -59 dBm
Related
So i've been trying to create a sentence-count function which will cycle through the following 'story':
let story = 'Last weekend, I took literally the most beautiful bike ride of my life. The route is called "The 9W to Nyack" and it actually stretches all the way from Riverside Park in Manhattan to South Nyack, New Jersey. It\'s really an adventure from beginning to end! It is a 48 mile loop and it basically took me an entire day. I stopped at Riverbank State Park to take some extremely artsy photos. It was a short stop, though, because I had a really long way left to go. After a quick photo op at the very popular Little Red Lighthouse, I began my trek across the George Washington Bridge into New Jersey. The GW is actually very long - 4,760 feet! I was already very tired by the time I got to the other side. An hour later, I reached Greenbrook Nature Sanctuary, an extremely beautiful park along the coast of the Hudson. Something that was very surprising to me was that near the end of the route you actually cross back into New York! At this point, you are very close to the end.';
And I realise the problem I'm having but I cannot find a way around this. Basically I want my code to return a the total sCount below but seeing as I've returned my sCount after my loop, it's only adding and returning the one count as a total:
const sentenceTotal = (word) => {
let sCount = 0;
if (word[word.length-1] === "." || word[word.length-1] === "!" || word[word.length-1] === "?") {
sCount += 1;
};
return sCount;
};
// console.log(sentenceTotal(story)) returns '1'.
I've tried multiple ways around this, such as returning sentenceTotal(word) instead of sCount but console.log will just log the function name.
I can make it return the correct sCount total if I remove the function element of it, but that's not what I want.
I don't see any loop or iterator which would go through story to count the number of occurrences of ., ?, or !.
Having recently tackled "counting sentences" myself I know it is a non-trivial problem with many edge cases.
For a simple use-case though you can use split and a regular expression;
story.split(/[?!.]/).length
So you could wrap that in your function like so:
const sentenceTotal = (word) => {
return word.split(/[?.!]/).length
};
let story = 'Last weekend, I took literally the most beautiful bike ride of my life. The route is called "The 9W to Nyack" and it actually stretches all the way from Riverside Park in Manhattan to South Nyack, New Jersey. It\'s really an adventure from beginning to end! It is a 48 mile loop and it basically took me an entire day. I stopped at Riverbank State Park to take some extremely artsy photos. It was a short stop, though, because I had a really long way left to go. After a quick photo op at the very popular Little Red Lighthouse, I began my trek across the George Washington Bridge into New Jersey. The GW is actually very long - 4,760 feet! I was already very tired by the time I got to the other side. An hour later, I reached Greenbrook Nature Sanctuary, an extremely beautiful park along the coast of the Hudson. Something that was very surprising to me was that near the end of the route you actually cross back into New York! At this point, you are very close to the end.';
sentenceTotal(story)
=> 13
There a several strange things about you question so I'll do it in 3 steps :
First step : The syntax.
What you wrote is the assignement to a const of an anonymous variable. So what it does is :
Create a const name 'sentenceCount'
To this const, assign the anonymous function (words) => {...}
Now you have this : sentenceCount(words){...}
And that's all. Because what you wrote : ()=>{} is not the calling of a function, but the declaration of an anonym function, you should read this : https://www.w3schools.com/js/js_function_definition.asp
If you want a global total, you must have a global total variable(not constant) so that the total isn't lost. So :
let sCount = 0; //<-- have sCount as a global variable not a const
function isEndOfSentence(word) {
if (word[word.length-1] === "." || word[word.length-1] === "!" || word[word.length-1] === "?") {
sCount += 1;
};
};
If you are forbidden from using a global variable (and it's best to not do so), then you have to register the total as a return of your function and store the total in the calling 'CountWords(sentence)' function.
function isEndOfSentence(words) {...}
callingFunction(){
//decalaration
let total;
//...inside your loop
total += isEndOfSentence(currentWord)
}
The algorithm
Can you provide more context as how you use you function ?
If your goal is to count the words until there is a delimiter to mark the end of a sentence, your function will not be of great usage .
As it is written, your function will only ever be able to return 0 or 1. As it does the following :
The function is called.
It create a var called sCount and set it to 0
It increment or not sCount
It return sCount so 1 or 0
It's basically a 'isEndOfSentence' function that would return a boolean. It's usage should be in an algorithm like :
// var totalSentence = 0
// for each word
// if(isEndOfSentence(word))
// totalSentence + totalSentence = 1
// endfor
Also this comes back to just counting the punctuation to count the number of sentence.
The quick and small solution
Also I tried specifically to keep the program in an algorithm explicit form since I guess that's what you're dealing with.
But I feel that you wanted to write something small and with as little characters as possible so for your information, there are faster way of doing this with a tool called regex and the native JS 'split(separator)' function of a string.
A regex is a description of a string that it can match to and when used can return those match. And it can be used in JS to split a string:
story.split(/[?!.]/) //<-- will return an array of the sentences of your story.
story.split(/[?!.]/).length //<-- will return the number of element of the array of the sentences of your story, so the sentence count
That does what you wanted but with one line of code. But If you want to be smart about you problem, remember that I said
Also this comes back to just counting the punctuation to count the number of sentence.
So we'll just do that right ?
story.match(/(\.\.\.)|[.?!]/g).length
Have fun here ;) : https://regexr.com/
I hope that helps you ! Good luck !
I have problems with the general recognition of subscript and superscript in text fragments.
Example-image:
I used Tesseract 4.1.1 with the training data available under https://github.com/tesseract-ocr/tessdata_best. The numerous options had default values except:
tessedit_create_hocr = 1 (to get result as HOCR)
hocr_font_info = 1 (to get additional font infos like font size)
hocr_char_boxes = 1 (to get character-based result)
The language was set to eng. Neither with page segmentation mode 3 (PSM_AUTO_OSD) nor 11 (PSM_SPARSE_TEXT) nor 12 (PSM_SPARSE_TEXT_OSD) the subscript/superscript was recognized correctly.
In the output the sub/sup-fragments were all more or less wrong:
"SubtextSub" is recognized as "Subtextsu,"
"SuptextSub" is recognized as "Suptexts?"
"P0" is recognized as "Po"
"P100" is recognized as "P1go"
"a2+b2" is recognized as "a+b?"
Using Tesseract for OCR is there a way to ...?
optimize subscript/superscript handling
get infos about recognized subscript/superscript (in the hocr-output - ideally for each character)
Working on the quality of the image as suggested in other questions/answers to this topic didn't really change anything.
Following these 2 links from the tesseract-google-newsgroup at first it really seemed to be a question of training:
link1 and link2.
But after doing some experiments I found out, that the used OEM_DEFAULT-OCR engine mode just doesn't bring up the needed information. I found a partial solution to the problem. Partial, because I now get most infos about sub/sup and also the recognized characters are right in most cases, but not for all characters.
Using the OEM_TESSERACT_ONLY-OCR engine mode (=the legacy mode) and some API methods provided by Tess4J I came up with the following java test class:
public class SubSupEvaluator {
public void determineSubSupCharacters(BufferedImage image) {
//1. initialize Tesseract and set image infos
TessBaseAPI handle = TessAPI1.TessBaseAPICreate();
try {
int bpp = image.getColorModel().getPixelSize();
int bytespp = bpp / 8;
int bytespl = (int) Math.ceil(image.getWidth() * bpp / 8.0);
TessBaseAPIInit2(handle, new File("./tessdata/").getAbsolutePath(), "eng", TessOcrEngineMode.OEM_TESSERACT_ONLY);
TessBaseAPISetPageSegMode(handle, TessPageSegMode.PSM_AUTO_OSD);
TessBaseAPISetImage(handle, ImageIOHelper.convertImageData(image), image.getWidth(), image.getHeight(), bytespp, bytespl);
//2. start actual OCR run
TessBaseAPIRecognize(handle, null);
//3. iterate over the result character-wise
TessResultIterator ri = TessBaseAPIGetIterator(handle);
TessPageIterator pi = TessResultIteratorGetPageIterator(ri);
TessPageIteratorBegin(pi);
do {
//determine character
Pointer ptr = TessResultIteratorGetUTF8Text(ri, TessPageIteratorLevel.RIL_SYMBOL);
String character = ptr.getString(0);
TessDeleteText(ptr); //release memory
//determine position information
IntBuffer leftB = IntBuffer.allocate(1);
IntBuffer topB = IntBuffer.allocate(1);
IntBuffer rightB = IntBuffer.allocate(1);
IntBuffer bottomB = IntBuffer.allocate(1);
TessPageIteratorBoundingBox(pi, TessPageIteratorLevel.RIL_SYMBOL, leftB, topB, rightB, bottomB);
//write info to console
System.out.println(String.format("%s - position [%d %d %d %d], subscript: %b, superscript: %b", character, leftB.get(), topB.get(),
rightB.get(), bottomB.get(), TessAPI1.TessResultIteratorSymbolIsSubscript(ri) == TessAPI1.TRUE,
TessAPI1.TessResultIteratorSymbolIsSuperscript(ri) == TessAPI1.TRUE));
} while (TessPageIteratorNext(pi, TessPageIteratorLevel.RIL_SYMBOL) == TessAPI1.TRUE);
} finally {
TessBaseAPIDelete(handle); //release memory
}
}
}
The legacy mode only works with 'normal' training data. Using the '-best' training data is bringing an error.
There is very little information on this topic.
One option to enhance sub/superscript character recognition (even if not the position itself) is by preprocessing the image, with cv2 / pil (also pillow) e.g., and then tesseract it.
See
How to detect subscript numbers in an image using OCR?
Related (but otherwise not answering the question):
https://www.mail-archive.com/tesseract-ocr#googlegroups.com/msg19434.html
https://github.com/tesseract-ocr/tesseract/blob/master/src/ccmain/superscript.cpp
what do you guys think about getting tesseract to recognize single letters?
Tesseract does not recognize single characters
I tried it with the option --psm 10
tesseract imTstg.png out5 --psm 10
but it did not seem to work. I am thinking about just running yolo to detect the single letters.
I would like to search text which includes specified word from stream data with google cloud dataflow.
In detail, I will deal with following two stream.
stream A: element of stream is "word"
stream B: element of stream is "text". and each text consists of "word". This text may have "word" on stream A
Many "text" flow into stream B frequently. On the other hand, "word" flow into stream A occasionally.
When "word" flow into stream A, I would like to search "text" which has "word" and flow into stream B after 5 minutes ago.
Example
time stream A : stream B
00:01 - this is an apple
00:02 - this is an orange
00:03 - I have an apple
00:04 apple <= "this is an apple" and "I have an apple" are found
00:05 this <= "this is an apple" and "this is an orange" are found
Can I search text with google cloud dataflow?
If I understand your question correctly, there are multiple ways to achieve something like what you want. I will describe two variations.
The basic idea in my example code is to use an inner join and SlidingWindows of five minutes. You can implement the join using ParDo side inputs or CoGroupByKey, depending on your data sizes.
Here is how you set up your inputs and windowing:
PCollection<String> streamA = ...;
PCollection<String> streamB = ...;
PCollection<String> windowedStreamA = streamA.apply(
Window.into(
SlidingWindows.of(Duration.standardMinutes(5)).every(...)));
PCollection<String> windowedStreamB = streamB.apply(
Window.into(
SlidingWindows.of(Duration.standardMinutes(5)).every(...)));
You may want to adjust the size of windows or period to meet your specification & performance needs.
Here is a sketch of how to do the join with side inputs. This will iterate over the entire five minute window of streamB for each element of streamA, so performance will suffer if windows get large.
PCollectionView<Iterable<String>> streamBview = streamB.apply(View.asIterable());
PCollection<String> matches = windowedStreamA.apply(
ParDo.of(new DoFn<String, String>() {
#Override void processElement(ProcessContext context) {
for (String text : context.sideInput()) {
if (split(text).contains(context.element())) {
context.output(text);
}
}
}
});
Here is a sketch of how to do this with CoGroupByKey by pre-splitting the text and joining each keyword with the lines that contain that keyword. There is similar logic in the TfIdf example included with the SDK.
PCollection<KV<String, Void>> keyedStreamA = windowedStreamA.apply(
MapElements
.via(word -> KV.of(word, null))
.withOutputType(new TypeDescriptor<KV<String, Void>>() {}));
PCollection<KV<String, String>> keyedStreamB = windowedStreamB.apply(
FlatMapElements
.via(text -> split(text).forEach(word --> KV.of(word, text))
.withOutputType(new TypeDescriptor<KV<String, String>>() {}));
TupleTag<Void> tagA = new TupleTag<Void>() {};
TupleTag<String> tagB = new TupleTag<String>() {};
KeyedPCollectionTuple coGbkInput = KeyedPCollectionTuple
.of(tagA, keyedStreamA)
.and(tagB, keyedStreamB);
PCollection<String> matches = coGbkInput
.apply(CoGroupByKey.create())
.apply(FlatMapElements
.via(result -> result.getAll(tagB))
.withOutputType(new TypeDescriptor<String>()));
The best approach will depend on your data. If you are OK with getting more matches than just the last five minutes you can tune the amount of data duplication in windows by enlarging your sliding windows and having a larger period. You can also use triggers to tune when output is produced.
My app uses a Dictionary
protected _categoryToValueDict:Dictionary = new Dictionary();
to map something to something else.
Now, at a certain point in the application, I need to remove a certain key from the Dictionary.
I implemented this simple method:
public function setCategoryNoValue( cat:TAModelCategory ):void {
// delete( _categoryToValueDict[ cat ] );
var old:Dictionary = _categoryToValueDict;
_categoryToValueDict = new Dictionary();
for ( var key:* in old ) {
if ( key != cat ) {
_categoryToValueDict[ key ] = old[ key ];
}
}
}
If I only use [description of the delete operator]
delete( _categoryToValueDict[ cat ] );
the app itself doesn't throw errors in normal mode. But as soon as I serialize its external data structure to an external source [currently SharedObject], the app isn't able to de-serialize it later on.
If I use the above coded manual iterative removal operation, the de-serialize operation works as expected and the model appears in the app.
The alternative should be identical. Shouldn't they?
Thus, my question: What's the difference between the two alternatives?
PS: This question might be related to my previous one.
UPDATE-1
Adobe explains on this page:
To make the object referenced by myObject eligible for garbage collection, you must remove all references to it. In this case, you must change the value of myObject and delete the myObject key from myMap, as shown in the following code:
myObject = null;
delete myMap[myObject];
Is suppose this to be a typo. Shouldn't it read like this:
delete myMap[myObject];
myObject = null;
Why pass a null-pointer to myMap as key?
Okay, I just spent a good two hours or so looking into this, which is way more than I planning on spending looking at this. But I was intrigued.
I think you may have uncovered a legitimate bug in ActionScript's AMF encoding (or in how the Dictionary class gets seralized via AMF). The bug effects anything that uses AMF, so the exact same bug is reproduceable with a ByteArray, so I'm going to use that for demonstration purposes.
Consider the following code:
var d:Dictionary = new Dictionary(false);
d["goodbye"] = "world";
d["hello"] = "world";
delete d["hello"]
var ba:ByteArray = new ByteArray();
ba.writeObject(d);
var len:uint = ba.position;
ba.position = 0;
for(var i:uint=0;i<len;i++) {
trace(ba.readUnsignedByte().toString(16));
}
The output will be:
11 05 00 06 0f 67 6f 6f 64 62 79 65 06 0b 77 6f 72 6c 64
Now what if we don't ever put the "hello" in as a key:
var d:Dictionary = new Dictionary(false);
d["goodbye"] = "world";
var ba:ByteArray = new ByteArray();
ba.writeObject(d);
var len:uint = ba.position;
ba.position = 0;
for(var i:uint=0;i<len;i++) {
trace(ba.readUnsignedByte().toString(16));
}
The output then is:
11 03 00 06 0f 67 6f 6f 64 62 79 65 06 0b 77 6f 72 6c 64
Notice that the length is exactly the same, however they differ in the second byte.
Now lets look at the serialization for if I don't delete "hello":
11 05 01 06 0b 68 65 6c 6c 6f 06 0b 77 6f 72 6c 64 06 0f 67 6f 6f 64 62 79 65 06 02
Notice that 05 in the second byte is the same as when we deleted it. I think this is specifying the number of items in the Dictionary. I say "I think" because I dug through the documentation on AMF0/3 for quite a while trying to figure out exactly whats going on here, because it doesn't seem like this should be the serialization for a Dictionary, but its fairly consistent, but I don't get it.
So I think that's why you are hitting an exception (specifically the "End of file" error), because its still thinks there should be another item in the dictionary that it should be de-serializing.
Your alternate method works because you are constructing a new Dictionary and populating it... Its "internal counter" is only ever increasing, so it works like a charm.
Another thing to note, that if you set d["Hello"] = undefined, it does not throw an exception, but the item does not get removed from the dictionary. The key gets serialized with a value of undefined in the AMF stream. So the resulting byte-stream is longer than if it was never there.
Using an Object doesn't seem to exhibit this same behavior. Not only doesn't not produce an error, the generated bytecode is more in line with the AMF0/3 documentation I could find from Adobe. And the resulting "key" is literally dropped from the serialization, like it was in fact never there. So I'm not sure what special case they are using for Dictionary (apparently the undocumented AMF3 datatype 0x11), but it does not play right with deleting items out of it.
It seems like a legit bug to me.
edit
So I dug around a bit more and found other people talking about AMF serilization of a Dictionary.
0x11 : Dictionary Data Type
0x05 : Bit code: XXXX XXXY
: If y == 0 then X is a reference to a previously encoded object in the stream
: If y == 1 then X is the number of key/val pairs in the dictionary.
So if this case 5&1 == 1 and 5>>1 == 2, so it's expecting two key/val pairs in the "bad" serialized version.
Correct syntax for the delete operator is like this:
delete _categoryToValueDict[ cat ];
Although using parenthesis seems to compile fine, it's not the correct way.
I have something like 40 million TIFF documents, all 1-bit single page duplex. In about 40% of cases, the back image of these TIFFs is 'blank' and I'd like to remove them before I do a load to a CMS to reduce space requirements.
Is there a simple method to look at the data content of each page and delete it if it falls under a preset threshold, say 2% 'black'?
I'm technology agnostic on this one, but a C# solution would probably be the easiest to support. Problem is, I've no image manipulation experience so don't really know where to start.
Edit to add: The images are old scans and so are 'dirty', so this is not expected to be an exact science. The threshold would need to be set to avoid the chance of false positives.
You probably should:
open each image
iterate through its pages (using Bitmap.GetFrameCount / Bitmap.SelectActiveFrame methods)
access bits of each page (using Bitmap.LockBits method)
analyze contents of each page (simple loop)
if contents is worthwhile then copy data to another image (Bitmap.LockBits and a loop)
This task isn't particularly complex but will require some code to be written. This site contains some samples that you may search for using method names as keywords).
P.S. I assume that all of images can be successfully loaded into a System.Drawing.Bitmap.
You can do something like that with DotImage (disclaimer, I work for Atalasoft and have written most of the underlying classes that you'd be using). The code to do it will look something like this:
public void RemoveBlankPages(Stream source stm)
{
List<int> blanks = new List<int>();
if (GetBlankPages(stm, blanks)) {
// all pages blank - delete file? Skip? Your choice.
}
else {
// memory stream is convenient - maybe a temp file instead?
using (MemoryStream ostm = new MemoryStream()) {
// pulls out all the blanks and writes to the temp stream
stm.Seek(0, SeekOrigin.Begin);
RemoveBlanks(blanks, stm, ostm);
CopyStream(ostm, stm); // copies first stm to second, truncating at end
}
}
}
private bool GetBlankPages(Stream stm, List<int> blanks)
{
TiffDecoder decoder = new TiffDecoder();
ImageInfo info = decoder.GetImageInfo(stm);
for (int i=0; i < info.FrameCount; i++) {
try {
stm.Seek(0, SeekOrigin.Begin);
using (AtalaImage image = decoder.Read(stm, i, null)) {
if (IsBlankPage(image)) blanks.Add(i);
}
}
catch {
// bad file - skip? could also try to remove the bad page:
blanks.Add(i);
}
}
return blanks.Count == info.FrameCount;
}
private bool IsBlankPage(AtalaImage image)
{
// you might want to configure the command to do noise removal and black border
// removal (or not) first.
BlankPageDetectionCommand command = new BlankPageDetectionCommand();
BlankPageDetectionResults results = command.Apply(image) as BlankPageDetectionResults;
return results.IsImageBlank;
}
private void RemoveBlanks(List<int> blanks, Stream source, Stream dest)
{
// blanks needs to be sorted low to high, which it will be if generated from
// above
TiffDocument doc = new TiffDocument(source);
int totalRemoved = 0;
foreach (int page in blanks) {
doc.Pages.RemoveAt(page - totalRemoved);
totalRemoved++;
}
doc.Save(dest);
}
You should note that blank page detection is not as simple as "are all the pixels white(-ish)?" since scanning introduces all kinds of interesting artifacts. To get the BlankPageDetectionCommand, you would need the Document Imaging package.
Are you interested in shrinking the files or just want to avoid people wasting their time viewing blank pages? You can do a quick and dirty edit of the files to rid yourself of known blank pages by just patching the second IFD to be 0x00000000. Here's what I mean - TIFF files have a simple layout if you're just navigating through the pages:
TIFF Header (4 bytes)
First IFD offset (4 bytes - typically points to 0x00000008)
IFD:
Number of tags (2-bytes)
{individual TIFF tags} (12-bytes each)
Next IFD offset (4 bytes)
Just patch the "next IFD offset" to a value of 0x00000000 to "unlink" pages beyond the current one.