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Google has released the cloud Vision API (Application interface) of the public beta. will help third party developers integrate image recognition and classification functions in their applications.
Google's technology can perform basic functions, such as extracting text from images. The real strength is in identifying
Java fingerprint recognition + Google Image Recognition Technology
Some time ago, when I saw this similar image search principle blog on Ruan Yifeng's blog, there was an impulse to implement these principles.
I wrote a demo of imag
" --post-file=test.flac -- header = "Content-Type: Audio/X-Flac; rate = 16000" "http://www.google.com/speech-api/v1/recognize? Xjerr = 1 client = chromium lang = ZH-CN maxresults = 1"
The test.example voice is converted into a local file and saved in googlespeechapi.txt:
{
"Status": 0,
"ID": "8f9d46231ac2dadee91d8d6ba1b57779-1 ",
"Hypotheses ":
[
{"Utterance": "That doesn't work.", "Confidence": 0.87555957}]
}
This is an early experience of usi
Ps:
Based on Java 1.8Version control: MavenYou need to get the corresponding project Api_key,secret_key before use, these parameters must be used when using the API, to generate Access_token.How to get these parameters: apply for a "generic word recognition" project at Baidu Developer Center, and then you can get these parameters.The preparation conditions are complete, and now the
This section corresponds to Google Open source TensorFlow object Detection API Object recognition System Quick start Step (i):Quick Start:jupyter notebook for off-the-shelf inferenceThe steps in this section are simple and do the following:1. After installing Jupyter in the first section, enter the Models folder directory at the Ternimal terminal to execute the c
the node matrix or the number of input Samples
# Fourth parameter: Fill method, ' same ' means full 0 padding, ' VALID ' means no padding
TensorFlow to realize the forward propagation of the average pool layer
Pool = Tf.nn.avg_pool (actived_conv,ksize[1,3,3,1],strides=[1,2,2,1],padding= ' same ')
# first parameter: Current layer node Matrix
# The second parameter: the size of the filter
# gives a one-dimensional array of length 4, but the first and last of the array must be 1
parseqrcodebitmap (String bi Tmappath) {//Resolution conversion type UTF-8 HashtableAnd then long press recognize QR code called Rgbluminancesource This classpublic class Rgbluminancesource extends Luminancesource {private byte bitmappixels[];p rotected Rgbluminancesource ( Bitmap Bitmap) {super (Bitmap.getwidth (), Bitmap.getheight ());//First, to get the image of the pixel array content int[] data = new Int[bitmap.getwidth () * Bitmap.getheight ()]
Public platform Message Interface Development image recognition-face recognition I. Preface
In the past few small applications, it seems that the response is not cool or hot, and everyone is not interested. Today, we will give you a bright eye: face recognition on the public platform.
Some time ago, I saw a report on
Image Recognition in various recognition Libraries
In-Spirit
Eugene zatepyakin open source stuff
Http://code.google.com/p/in-spirit/w/list
Face Recognition
Http://code.google.com/p/vjdetector/
Flash Kinect
Http://code.google.com/p/as3openni/
Face-recognition-library-as3
Integrate the google map api with the GOOGLE Search API. I wrote a class in object-oriented mode, passed a latitude and longitude, and automatically obtained nearby information through GOOGLE LOCAL SEARCH. Such as restaurants and scenic spots, which are marked on the map in
Integrate the google map api with the GOOGLE Search API. I wrote a class in object-oriented mode, passed a latitude and longitude, and automatically obtained nearby information through GOOGLE LOCAL SEARCH. Such as restaurants and scenic spots, which are marked on the map in
, deep learning can reach 99.47% recognition rate [8].While the academic community has received extensive attention, deep learning has also had a huge impact in industry. 6 months after Hinton's team won the Imagenet competition, Google and Baidu released new search engines based on image content. They followed the deep learning model used by Hinton in the Imagen
traditional computer vision methods, hand-designed features, and the difference in accuracy between them was no more than 1%. The degree of accuracy of the Hinton research group exceeds 10% in the second place (see table 1). This results in the field of computer vision generated a great shock, triggering the upsurge of deep learning. Another important challenge in the field of computer vision is human face recognition. Studies have shown that the
License plate Recognition The private cloud is the server version of the license plate recognition software, the use of OCR algorithm to identify the car, the difference is by the license plate cloud recognition deployed in the customer's own server or public server.The following focuses on the private cloud license plate rec
Google as the IT giant, voice search body sense is very good, fast and accurate recognition. Google's voice search can be widely used with lbs-based Android applications, call the Google API to get search results, and then do what you want based on this result.To begin with, let's start with a formal introduction to G
API Shutdown nears, What Are Your Options?
When Google Earth API closes recently, what is your choice.
The previously popular Google earth API is being deprecated and are due to shut down in early 2016,
The previously popular Google
recognition accuracy is very high, and it is suitable for text speech recognition. Provides speech recognition in multiple languages. ?any platform can be accessed, easy to use. -Main Disadvantages?APInot be open to know the specifics of the development. ?The recognition engine is located on the server side, and the s
common feature requests we 've heard on Android is supportMap fragments. With this new API, adding a map to your activity is as simple:
Check out this image from updated trulia Android app (which goes live tomorrow), that users can useTo search for a place to buy or rent in 3D.
The new API is simpler to use, so that creating markers and info windows is easy. po
Google says it will sponsor an AI research and development group, and will work together to develop character recognition technology in the future.
According to CNET, the project is an open resource type named Ocropus, with several goals, including "developing high-end, easy-to-use handwriting recognition systems that translate handwritten documents into computer
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