face_detection | using caffemode which is provided by shiqi yu | Machine Learning library

by daixiangzi Python Version: Current License: No License

X-Ray Key Features Code Snippets Community Discussions(10)Vulnerabilities Install Support

kandi X-RAY | face_detection Summary

face_detection is a Python library typically used in Artificial Intelligence, Machine Learning, Deep Learning, Pytorch applications. face_detection has no bugs, it has no vulnerabilities and it has low support. However face_detection build file is not available. You can download it from GitHub.

using caffemode which is provided by shiqi yu caffemodel link:in this section,i only write a test.py code run face detection.

Support

Quality

Security

License

Reuse

Support

face_detection has a low active ecosystem.

It has 14 star(s) with 3 fork(s). There are 2 watchers for this library.

It had no major release in the last 6 months.

There are 2 open issues and 1 have been closed. There are no pull requests.

It has a neutral sentiment in the developer community.

The latest version of face_detection is current.

Quality

face_detection has no bugs reported.

Security

face_detection has no vulnerabilities reported, and its dependent libraries have no vulnerabilities reported.

License

face_detection does not have a standard license declared.

Check the repository for any license declaration and review the terms closely.

Without a license, all rights are reserved, and you cannot use the library in your applications.

Reuse

face_detection releases are not available. You will need to build from source code and install.

face_detection has no build file. You will be need to create the build yourself to build the component from source.

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face_detection Key Features

No Key Features are available at this moment for face_detection.

face_detection Examples and Code Snippets

No Code Snippets are available at this moment for face_detection.

Community Discussions

Trending Discussions on face_detection

Tensor Tensor("flatten/Reshape:0", shape=(?, 2622), dtype=float32) is not an element of this graph

!empty() in function 'detectMultiScale'

multi-threading, what is wrong with my code

Change specific NumPy array to be coordinate

How do I test event trigger cloud function?

unindent does not match any outer indentation level in face app

Node child_process await result

Integrating Native code with CameraX to Custom React Native Component Fails

Google Vision Text detection API give a different result compared to their demo page

License plate recognition using GCP's Cloud Vision

QUESTION

Tensor Tensor("flatten/Reshape:0", shape=(?, 2622), dtype=float32) is not an element of this graph

Asked 2021-May-24 at 09:55

Hello StackOverFlow Team: I built a model based on (Vgg_Face_Model) with weights loaded (vgg_face_weights.h5). Note that I use tensorflow-gpu = 2.1.0 , and keras=2.3.1 , with Anaconda 3 create it as interpreter and used with pycharm But the code shows an error in the part :

...

ANSWER

Answered 2021-May-24 at 09:55

from tensorflow.python.keras.backend import set_session
sess = tf.Session()

#This is a global session and graph
graph = tf.get_default_graph()
set_session(sess)


#now where you are calling the model
global sess
global graph
with graph.as_default():
    set_session(sess)
    input_descriptor = [model.predict(face), img]

Source https://stackoverflow.com/questions/67659336

QUESTION

!empty() in function 'detectMultiScale'

Asked 2021-May-19 at 08:02

I run my code in Pycharm Community Edition 2020.1.1 x64 and I add my haar_face.xml and this py file in the same folder. I also tried to google and add some stuffs like cv.data.haarcascade+ or copy the complete path of the xml file but it still shows me the error below.

CODE

...

ANSWER

Answered 2021-May-19 at 07:42

The path is wrong in this line:

Source https://stackoverflow.com/questions/67598695

QUESTION

multi-threading, what is wrong with my code

Asked 2021-Apr-08 at 19:57

I was trying to make faster my frames in opencv, it was so slow using it normal, so I decided to ask it here Make faster videocapture opencv the answer was to use multi threading to make it faster, so I code it like this

...

ANSWER

Answered 2021-Apr-08 at 19:57

Your VideoStream class's init looks ok, but I think you might have better luck creating a cv2 VideoCapture object in the init as well:

Source https://stackoverflow.com/questions/67010610

QUESTION

Change specific NumPy array to be coordinate

Asked 2021-Mar-13 at 21:57

I want to change the NumPy array from [x0 y0 x1 y1] to be [(y0, x0) (x1, y1)].

I already tried many things but still not found the right way.

This was my code:

...

ANSWER

Answered 2021-Mar-13 at 21:57

Example for converting NumPy array into a list of two tuples:

Source https://stackoverflow.com/questions/66616464

QUESTION

How do I test event trigger cloud function?

Asked 2021-Mar-01 at 08:16

I want to do unit testing on cloud functions, however, the function itself is an event trigger function that contains some helper functions. I want to test those helper functions as well. Here is the code sample

...

ANSWER

Answered 2021-Mar-01 at 08:16

I actually found a way of testing this. I used functions-framework for the testing. You can find the answer https://github.com/neu-self-image-experiments/sie-backend#test-guidelines

Source https://stackoverflow.com/questions/66297468

QUESTION

unindent does not match any outer indentation level in face app

Asked 2020-Dec-27 at 23:03

I have here a script and i keep getting and indentation error but i cant figure out why

...

ANSWER

Answered 2020-Dec-27 at 16:18

Answer
The indentation issue is most likely caused by using both tabs and spaces for indentation. The PEP 8 formatting rules state to use spaces for indents. In certain IDEs you can set spaces to convert to tab, which can save you from the headaches of python syntax.

References and Additional Links
PEP 8: https://www.python.org/dev/peps/pep-0008/#indentation
Similar Stack Overflow Question: IndentationError: unindent does not match any outer indentation level

Source https://stackoverflow.com/questions/65467626

QUESTION

Node child_process await result

Asked 2020-Sep-30 at 22:22

I have a async function which makes a face_detection command line call. It's working fine otherwise, but I can't make it to wait for the response. Here is my function:

...

ANSWER

Answered 2020-Sep-30 at 22:22

I think you must convert child.exec into a Promise and use it with await. Otherwise the async function is not waiting for child.exec result.

To make it easy you can use Node util.promisify method: https://nodejs.org/dist/latest-v8.x/docs/api/util.html#util_util_promisify_original

Source https://stackoverflow.com/questions/64135194

QUESTION

Integrating Native code with CameraX to Custom React Native Component Fails

Asked 2020-Sep-28 at 10:30

Hello I have an app that used now deprecated Camera module in android for displaying the camera view and drawing filters onto it using mlkit face detection. Recently we've decided to upgrade it to CameraX, I did all the necessary steps to make it work as a separate android app and it works. When I want to incorporate it to our existing Custom React Native module no matter what I do, it doesn't show anything on the screen. I've checked the view sizes and they seem to be ok. Below is the code I use to start the camera module.

...

ANSWER

Answered 2020-Sep-28 at 10:30

The issue happens because the relative layout is not resized after being added to the scene. The workaround is not mine, but I could not find where it was from right now so I'll just leave it here in case someone else is having the similar issue. I solved the issue by calling the layoutHack in the constructor of my RelativeLayout

Source https://stackoverflow.com/questions/63896520

QUESTION

Google Vision Text detection API give a different result compared to their demo page

Asked 2020-May-22 at 11:59

I want to use their OCR function with Google Vision but like a lot of people here, my result are not the same when I use their HTTP API and their demo page, on their demo page they show the json request and result.

I used the same json request and I have a different result, their demo page is more accurate than their API.

Their demo page : https://cloud.google.com/vision/docs/drag-and-drop

Their API URL : https://vision.googleapis.com/v1/images:annotate?key=YOURAPIKEY You can pass their json generated on their demo to test

The only difference is I use imageUri to send my file and google use their local storage (content param)

With their HTTP API I can catch only the first line but not the second but their demo catch both of them.

Any clue ?

My test image : http://maxence.me/labs/others/c668d1346a74873b8773d7ca19d7feaf_1589063679_0_18.png

My JSON :

...

ANSWER

Answered 2020-May-15 at 13:36

Today, their HTTP API give the same result as their demo page... maybe their version got delay or Google is there ? :o

Source https://stackoverflow.com/questions/61795788

QUESTION

License plate recognition using GCP's Cloud Vision

Asked 2020-Apr-29 at 01:04

We are developing a mobile app that will allow users to upload images that will be stored in a GCP bucket. However before saving to the bucket we want to blur out any faces and license plates that may be present. We have been using a call to GCP's Cloud Vision service to annotate the image for faces and this has worked quite well. However license plates annotation has turned out to be more challenging. There is no option to detect license plates specifically but instead we seem limited to text-detection which catches license plates, but also all other text that is in image. This is not what we want.

Any pointers on how we might better narrow down the text-recognition to just license plates?

Here's an example of the Python code we are currently using to detect and gather annotation data for faces and text:

...

ANSWER

Answered 2019-Jul-30 at 17:53

You have to create a custom model, upload your training set of images (license plates in this case) and train it to generate the model, then you can use that model to send the images and get the information back...

Take a look at Google Object Detection

Source https://stackoverflow.com/questions/57277319

Community Discussions, Code Snippets contain sources that include Stack Exchange Network

Vulnerabilities

No vulnerabilities reported

Install face_detection

You can download it from GitHub.
You can use face_detection like any standard Python library. You will need to make sure that you have a development environment consisting of a Python distribution including header files, a compiler, pip, and git installed. Make sure that your pip, setuptools, and wheel are up to date. When using pip it is generally recommended to install packages in a virtual environment to avoid changes to the system.

Support

For any new features, suggestions and bugs create an issue on GitHub. If you have any questions check and ask questions on community page Stack Overflow .

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