Can we make an image recognition system that is (rotation, scale, brightness, saturation) Invariant?
Of course, it can be achieved by several techniques such as SIFT, SURF or the ConvNets.But it's interesting to note that transfer learning is the best approach to achieve reliable invariant recognition systems.For example I teach a recognition system to recognize object A, lets assume there is limited training data for object A so that the system is incapable of generalizing well after training. Now the same system is also taught to recognize object B but this time around there is enough data for object B.A typical recognition system will find it hard to recognize object A in novel situations such as when A is rotated but it will do much better on B because there was enough data for B.The system supporting transfer learning on the other hand will also improve the model for A thus it will transfer knowledge about B to A and vice versa thus it could be able to perform even better on both A and B.Thus in my new system called IRIS (Integrated Recognition and Inference System) there is the use of transfer learning to learn transformation invariant world models similar to the way humans recognize stuff. For example if I want the system to develop rotation (both in-plane and out-plane rotations) invariant features, instead of designing an algorithm to explicitly handle rotations the systems learns by observing a multitude of other world objects in different rotational poses.Afterwards the system can learn to recognize any other different object in different rotational poses in one-shot just by transferring the knowledge from previous experience. Not only does this work for rotation it applies to many effects such as lighting changes e.t.c.And I have already personally designed and developed a scale, rotation and translation invariant instance-level object recognition system before, it is used in this panorama app similar to Autostitch. I explicitly designed it to have this scale, rotation and translation invariant behavior.It's just that my newer IRIS does it differently and better by transfer learning.Hope this helps.
How do image recognition algorithms work?
To perform an image recognition you have to find a way to represent an image with certain features. Which ones you choose highly affects the final results your algorithm will obtain.Some basic pre-processing methods that might be applied to images are adjusting brightness and contrast (histogram equalisation), removing noises (mean / median filtering, discrete convolution, FFT), sharpening (discrete convolution, FFT), edge or blob detection methods (using gradients or laplacians).To distinguish an object from a background (i.e. to count objects) some thresholding methods (global / adaptive) might be use. They are usually followed by morphological operations (erosion / dilation / opening / closing) to improve the selection results.More advanced feature extraction methods might be calculating Gray-Level Co-Occurance Matrix (GLCM) or Zernike Polynomials.When you will be able to transform your image with a variety of different high-quality features feed them into classification algorithm and you're done.
How do I extract a particular object from images using OpenCV?
There are multiple aspects. you will first have to answer few questions like:Dataset: Do you have a good dataset to work with? Though good is a subjective term, it can be further broken down into questions like number of samples, object of interest, occlusions if any, confusing objects, etc."Particular" Object: What is this object, can it be segmented, does it have a definite bounding box, or is my object even have similar shape everywhere?Accuracy: How accurate you want your results would be? Optimistic answer would be 100%, but is that much accuracy required/possible?Speed: Extraction speed as well as, if you use training testing framework as others suggested, then training speed.Is it worth: Check out if there is easy solution already available, assuming you are trying to build some demo. If you are doing a research then that is a different ball-game altogether, and you can explore many things. BTW, extraction is usually better understood by the term segmentation in the image processing community. If you provide further details, me/others here would be glad to help you.
How can I make an app that uses image recognition with TensorFlow that identifies different types of plants?
There are various ways you can achieve this. One of the simplest ones I can think of is to retrain the “Inception model”[1] by applying the technique called “transfer learning[2].”Your classes are the different types of plants, which are to be classified; therefore, you would require pictures of the respective plant for retraining the last layer of inception model. Now you can get pictures by just searching on Google and batch download those pictures. There are some nice extensions out there for this purpose, like Bulk Image Downloader, Fatkun Batch Download Image etc.There are bunch of good videos on YouTube as well, which explains how to retrain Inception model using TensorFlow and few other tools, like(one by Siraj[3]).Now let’s talk about the “app” part of your question.Recently(not quite recent though), TensorFlow has introduced the APIs for Android and iOS under the umbrella of TensorFlow Mobile[4]. By virtue of that, you can now use your trained model(mentioned above) and classify things in real-time.You do not need to train your model on a device(iOS/Android). All you need is to train your model on your personal computer(Desktop/Laptop) and import the model in your project of respective mobile-OS(like xCode Project for iOS, and AndroidStudio Project for Android). Again, this step is extensively explained in the following link by TensorFlow.Footnotes[1] How to Retrain Inception's Final Layer for New Categories | TensorFlow[2] Transfer Learning - Machine Learning's Next Frontier[3] Build a TensorFlow Image Classifier in 5 Min[4] TensorFlow
Which is the fastest Image Loading Library For Android?
Hello,Glide is fast and efficient image loading library for Android that wraps image downloading, resizing, memory and disk caching, and bitmap recycling into one simple and easy to use interface. By default, Glide includes an implementation for fetching images over http based on Google's Volley project for fast, parallelized network operations on Android.Source: Page on android-arsenal.com
Is there a way to insert and resize multiple images in MS Excel?
in case you employ Picasa there is an export decision, in the export decision you are able to export all chosen pictures and state the size you want them to export to. go with them, then Export them to a sparkling folder and there you bypass in that new folder is each and each and every of the documents on the size you particular. there is an decision to keep aspect ratio, it type of feels from what you try to do you've that container set. Untick the keep aspect ratio container to boot, or you'll finally end up with an similar image sizes that your getting already. What aspect ratio does is this - once you've a image as an get mutually it is 10 x 10 and also you tried to resize it to at least one hundred x ninety you need to do it, yet you does no longer take care of aspect ratio, hence the top of the hot image will be smaller than the former image, and what you'll see is that persons in the picture would look quite fatter. yet in case you resized it to at least one hundred x one hundred you would nonetheless take care of aspect ratio as in the unique (10x10) you've a million pixel down for each a million pixel throughout the time of), in the hot one you nonetheless have a million pixel down for each a million pixel throughout the time of (in trouble-free terms large difference is you've prolonged the size through 10. What it appears that evidently you try to do is take a 4:3 image and turn it right into a 16:9 image. you need to attempt this in case you tell the application equipment to ignore aspect ratio, yet once you've keep aspect ratio checked it is going to keep the picture at 4:3. that is an similar as at the same time as your watching an previous movie on a present day widescreen television, you are able to placed it into widescreen mode, yet you'll discover anybody in the movie looks to have placed on some pounds 'cos you've stretched them to in good structure the show ignoring aspect ratio.
How are the JPEG and the RAW versions of an image (JPEG and RAW mode) separated, as only one image can be seen on the camera preview? I have to use both.
It seems- to me that you are speaking of a camera phone and not a DSLR. This answer reflects that.Most Android phones which shoot RAW+JPEG tend to store the RAW files and the JPEG files in different folders. The camera preview (and your Gallery or Photos app) tend to only look in the JPEG folder and show the JPEG images in preview, etc.On phones where the JPEGs and RAWs are saved in the same folder, chances are good that your Gallery/Photo app ignores RAW images by default, only showing you the JPEG images. This is generally fine since the RAW images are really only well suited for post processing (PP) and chances are that you want to do that on a larger screen with color profiles loaded.Also, because of their much larger sizes, Google Photo, et al, typically do not upload the RAW images to the cloud. You have to typically download them from your phone to your computer via USB connection to be able to manipulate them.There are some apps which allow RAW manipulation on your phone but they are usually not quite as capable and the few which are, are still better used on a larger screen with better color than a typical mobile phone screen.I shoot RAW+JPEG on my OnePlus One (Cyanogen Mod, 6.0.1). I download using USB through Digikam. I process with DarkTable or RawTherapee. Images sent directly from my phone to others are always the JPEG images. The OnePlus One camera app (and the other camera apps I have which record the RAW data) stores the RAWs in a separate folder from the JPEGs. Most other 3rd party camera apps tend to only store the JPEGs (as far as I can tell).
What is the best face recognition software?
Best in what respect? Granted you are seeking the “best facial recognition” - which is an ongoing competition anyone can look up at Face Recognition Vendor Test (FRVT); however, facial recognition software comes in a variety of forms, each related to a different application and purpose. What are you trying to do?Disclaimer: I develop facial recognition software for a leading FR vendor named CyberExtruder, Inc. Our software is the underlying FR engine for multiple FR vendor as well.The FR field offers various solutions, each expecting your needs to fit their solution. At CyberExtruder we do not expect to have any idea what you are trying to do, nor do we try to fit your needs into our solution. Beyond offering a consistently top ranking FR solution (ranked via the Facial Recognition Vendor Test) our software is remarkably fast (25M facial compares per second per 3.4 GHz core) and is available asan SDK, meaning the software you create is entirely local;as a server hosting an API, meaning you can write solutions similar to most on-line FR offerings, but some FR vendor is not hosting your sensitive FR database, you are, with the security level you want;as a workstation application, where everything is still local, and the operator is anyone from a security guard to a forensic analyst.Of course, the SDK integrates with the API which integrates with any number of local and remote workstation instances to create any level of hybrid, mesh-connected self healing distributed FR authentication, tracking, and analysis system one could dream of having. Plus our software will run perfectly fine on a $99 Intel Compute Stick as well as a laptop, desktop, or dedicated multi-core server.We’re not just providing damn good, top ranking FR. We’re providing a means to start with an easy off the shelf solution, progress your and your organization’s understanding and points of advantage with easy to develop and integrate extensions into Excel or really any other software with ease, and when the time comes for a strategic and/or high value project requiring FR, you’ll have the experience and confidence from using our self-same solutions in smaller footprints. We take real care in providing multi-tiered scaling solutions, where “scale” in not just scaling performance, but methods of integration, as well as varieties of hardware our solutions may be deployed.
Which is the best software which detect duplicate photos in windows?
Duplicate photos are a big pain and removing them manually is the bigger issue. I find PicBackMan to be one of the best Windows as well as Mac application to automatically remove duplicate photos. It has got many amazing features such as:100 dedupe allowed in Free TrialDe-dupe Photos on your computer instantlyDe-dupe online Photos from Flickr, SmugMug and FacebookChecksum based de-dupe ensures correct de-dupe even if photo file names are sameOption to Delete Duplicates or Move them to a folder.
Does the new Google Photos detect duplicates?
Google Photos can skip uploading exact duplicates like burst shots, but does not have a feature to scan/search/group duplicate photos. Also, it cannot detect similar or nearly identical ones.Try one of these apps on Android to detect duplicates and similar photos from your phone gallery:Qupiq - Compare & Delete Duplicate Photos - Scanning is very fast. Different folders/albums can be selected for scan. Gives option for comparison between similar photos to find the best and delete the rest. Option for favoriting/star marking photos.- Qupiq - Compare & Delete Duplicate Photos - Apps on Google PlayDuplicate Files Fixer - Widely used. Option for detecting duplicate files as well. - Duplicate Files Fixer and Remover - Apps on Google PlayRemo Duplicate Remover - Good user interface. Have iOS version as well. Remo Duplicate Photos Remover - Apps on Google PlayDuplicates Remover - Duplicates Remover - Apps on Google PlayThese days people take a lot of photos of the same thing, just to get the best shot. All these similar ones clog up phone space and further make it difficult to choose the best among those for sharing on social media.Use the above tools to keep your gallery clean by removing unwanted photos.All of the above have great reviews/ratings and thousands of users.Give them a try. Hope you find them useful!