iitzco / faced Goto Github PK

How can I train it on a dataset I have?

How was faced trained on the the WIDER FACE dataset and how was the dataset prepared?

Hi, thanks a lot for open-sourcing faced, this is awesome!

I have two questions:

1. In the predict method, do you have any particular reason for not returning the probability as well?

`

def predict(self, frame, thresh=0.85):
    input_img = cv2.resize(frame, (YOLO_SIZE, YOLO_SIZE)) / 255.
    input_img = np.expand_dims(input_img, axis=0)

    pred = self.sess.run([self.prob, self.x_center, self.y_center, self.w, self.h], feed_dict={self.training: False, self.img: input_img})

    bboxes = self._absolute_bboxes(pred, frame, thresh)
    bboxes = self._correct(frame, bboxes)
    bboxes = self._nonmax_supression(bboxes)

    return bboxes`

2. Related to question 1, is there a convenient way to get the prob/detection score for the predicted image?

Thank you so much.

For use with TensorFlow 2.0 I changed first line of faced/detector.py from :

import tensorflow as tf

to

import tensorflow.compat.v1 as tf

and it works. I know it's not ideal, but it works.

Hello!
Thanks for the project, it works for me.
But I have strange results with my GTX 1080 Ti.
For some reason when I install Tensorflow with CUDA support and check GPU usage in MSI Afterburner, it shows that 10.6 of 11 Gb video memory is used. And this is not a training mode - I just use these already trained models.
Does that mean that it really needs so much video memory or this program just fills all the memory a video card provides?
Will this work on some GT 730 4G GPU as well? Or it will be not enough video memory?
How much video memory does the module require?
Thanks!

Is there a way to change the camera(like where's the videocapture)?

Please share the pipeline configuration file.

this was my code when i used cascade file

`
import cv2
import numpy as np
import os

def f_s():

trainer = r'C:\Users\User\Documents\jarvis\face recognition\trainer'

recognizer = cv2.face.LBPHFaceRecognizer_create()
recognizer.read(trainer + '/trainer.yml')
cascadePath = r'C:\Users\User\Documents\jarvis\cascades\data\haarcascade_frontalface_default.xml'
faceCascade = cv2.CascadeClassifier(cascadePath)

font = cv2.FONT_HERSHEY_SIMPLEX

#iniciate id counter
id = 0

# names related to ids: example ==> mark : id=1,  etc
names = ['None','Mark'] 

# Initialize and start realtime video capture
cam = cv2.VideoCapture(0)
cam.set(3, 640) # set video widht
cam.set(4, 480) # set video height

# Define min window size to be recognized as a face
minW = 0.1*cam.get(3)
minH = 0.1*cam.get(4)



while True:
    ret, img =cam.read()
    img = cv2.flip(img, 1) # Flip vertically
    gray = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    
    faces = faceCascade.detectMultiScale( 
        gray,
        scaleFactor = 1.2,
        minNeighbors = 5,
        minSize = (int(minW), int(minH)),
    )

    for(x,y,w,h) in faces:
        cv2.rectangle(img, (x,y), (x+w,y+h), (0,255,0), 2)
        id, confidence = recognizer.predict(gray[y:y+h,x:x+w])

        # Check if confidence is less them 100 ==> "0" is perfect match 
        if (confidence < 100):
            id = names[id]
            confidence = "  {0}%".format(round(100 - confidence))
        else:
            id = "unknown"
            confidence = "  {0}%".format(round(100 - confidence))
        
                    
        if 'Mark' == id:
            A = '18'
        else:
            print('age: unknon')

        cv2.putText(img, str(id), (x+5,y-5), font, 1, (255,255,255), 2)
        cv2.putText(img, str(confidence), (x+65,y-5), font, 1, (255,255,0), 1)   
        cv2.putText(img, str(A), (x+25,y+h+23), font, 1, (255,255,0), 1)

    cv2.imshow('face recognition',img) 
    
    
    k = cv2.waitKey(10) & 0xff # Press 'ESC' for exiting video
    if k == 27:
        break

# Do a bit of cleanup
print("\n [INFO] Exiting Program and cleanup stuff")
cam.release()
cv2.destroyAllWindows()

if name == "main":
f_s()
`

is there a way of me adding my name the way i did above in the face code thing

Im trying to call face_detector.predict(rgb_img, thresh) just about 100 times/second and each time it causes memory increment just around 1.3-8.0 Mb.

    def crop_faces_from_numpy_image(self, numpy_rgb):
        bboxes = self.face_detector.predict(numpy_rgb, self.thresh)
        cropped_images_array = []

        for bbox in bboxes:
            xc = bbox[0]
            yc = bbox[1]
            w = bbox[2]
            h = bbox[3]

            face = self.cv2_image[yc - h:yc + h, xc - w:xc + w]
            if len(face) > 0:
                resized = cv2.resize(face, dim)
                cropped_images_array.append(resized)

        return cropped_images_array

    def numpy_image_from_bytes(self, data):
        cv2img = cv2.imdecode(np.frombuffer(data, np.uint8), -1)
        self.cv2_image = cv2img
        np_rgb = cv2.cvtColor(cv2img.copy(), cv2.COLOR_BGR2RGB)
        return np_rgb

Line #    Mem usage    Increment  Occurrences   Line Contents
=============================================================
    23    796.0 MiB    796.0 MiB           1   @profile
    24                                         def crop_and_save(barr_img):
    25    797.3 MiB      1.3 MiB           1       np_arr = fd_worker.numpy_image_from_bytes(barr_img)
    26    805.3 MiB      8.0 MiB           1       cropped_arr = fd_worker.crop_faces_from_numpy_image(np_arr) - here is leakage
    27    805.5 MiB      0.2 MiB           1       fd_worker.save_images(cropped_arr)
    28    805.5 MiB      0.0 MiB           1       del np_arr
    29    805.5 MiB      0.0 MiB           1       del cropped_arr
    30    805.5 MiB      0.0 MiB           1       gc.collect()

Python 3.8

'faced' is not recognized as an internal or external command,
operable program or batch file.

why ???????

Hi everyone.
I could n't install faced on my Windows , I got this error and didn't understand it .
I appreciate if you could help me to install and use it

""
C:\Users\user1\Desktop\31Dec2018\faced>pip install git+https://github.com/iitzco/faced.git
Collecting git+https://github.com/iitzco/faced.git
Cloning https://github.com/iitzco/faced.git to c:\users\user1\appdata\local\temp\pip-req-build-ei3jp_f7
Complete output from command python setup.py egg_info:
Traceback (most recent call last):
File "", line 1, in
File "C:\Users\user1\AppData\Local\Temp\pip-req-build-ei3jp_f7\setup.py", line 14, in
long_description=readme(),
File "C:\Users\user1\AppData\Local\Temp\pip-req-build-ei3jp_f7\setup.py", line 6, in readme
return f.read()
File "C:\Users\user1\Downloads\WinPython-64bit-3.6.2.0Qt5\python-3.6.2.amd64\lib\encodings\cp1252.py", line 23, in decode
return codecs.charmap_decode(input,self.errors,decoding_table)[0]
UnicodeDecodeError: 'charmap' codec can't decode byte 0x8f in position 19: character maps to
""

Thank you

This work is very nice, and I was wondering if there is a paper attached with it so I can read it in more detail. Also, what was the testing accuracy on the Wider face dataset after reducing YOLO to your network?

Faiz  localhost  ~  GitRepos  Faced  🔥  pip3 install git+https://github.com/iitzco/faced.git
Collecting git+https://github.com/iitzco/faced.git
Cloning https://github.com/iitzco/faced.git to /tmp/pip-req-build-cqyujtbf
Collecting numpy (from faced==0.1)
Downloading https://files.pythonhosted.org/packages/3d/10/62224c551acfd3a3583ad16d1e0f1c9e9c333e74479dc51977c31836119c/numpy-1.16.0-cp37-cp37m-manylinux1_x86_64.whl (17.3MB)
100% |████████████████████████████████| 17.3MB 443kB/s
Collecting tensorflow (from faced==0.1)
Could not find a version that satisfies the requirement tensorflow (from faced==0.1) (from versions: )
No matching distribution found for tensorflow (from faced==0.1)

Hi Ivan,

I used your face_detection model on some low resolution and dark contrast images such as the ones taken through cctv feed. The results aren't good on such images, Can you suggest resources which would be good for such kind of images, I'm okay with gpu usage.

Thanks,
Aditya

Hello, I've tried to load model for face_yolo.pb
However, it shows the following messages:

ValueError: No op named IteratorFromStringHandle in defined operations.

Could you please help comment it?
Thanks

Hey @iitzco

I think this is an awesome project and great example of using tensorflow in a fast, reliable and CPU backed way.

In an effort to better understand how to create Tensorflow + Rust apps I started to port faced to Rust here: https://github.com/drbh/faced-rs

I have most of the core logic completed (load and run the two models) but need to finish writing the non_max and IOU functions.

Just wanted to share the repo and thank you for the awesome project! Also I would love to hear any feedback you have - or ways that faced-rs can be improved 😁

Hi! This looks really promising and interesting, good work! Would it be possible to get the actual trained model either in Keras format (.h5) or in ONNX? I'd like to use the model in MATLAB, but I can only import either Keras or ONNX formats.

Unless im mistaken thus repository only contains the pretrained tensorflow1.x models of the the FaceDetector (face-yolo.pb) and FaceCorrector. i was wonderign if i could have a look at the actual code, and dataset used to traij these models

Can you tell me how to extract the weights of your trained dataset?
please upload the training scripts i would like to create my yolo for eye detection.

i am beginner of deep learning and i know the previous issue solution about which is how to train on your blog but i have a question that your explanation of auxilary network is not clear. Is auxilary network concatenated by main network? or independtly? so i want to know how to train main architecture and auxilary network clearly and i have one more question that how to use on GPU environments when inference step?

I would like to train this model for Person detection.
Please help with the steps.

From the looks of it, nothing should prevent it from running on Jetson. But, I am curious if have some performance numbers on Jetson. Thanks

OS: Windows 10
Python v3.6.x

E:\clients\Assets\FR_Infogen_v3\IGL\code>pip install git+https://github.com/iitzco/faced.git
Collecting git+https://github.com/iitzco/faced.git
  Cloning https://github.com/iitzco/faced.git to c:\users\diksha\appdata\local\temp\pip-req-build-5ibodt8c
    Complete output from command python setup.py egg_info:
    Traceback (most recent call last):
      File "<string>", line 1, in <module>
      File "C:\Users\Diksha\AppData\Local\Temp\pip-req-build-5ibodt8c\setup.py", line 14, in <module>
        long_description=readme(),
      File "C:\Users\Diksha\AppData\Local\Temp\pip-req-build-5ibodt8c\setup.py", line 6, in readme
        return f.read()
      File "D:\ai\envs\face3\lib\encodings\cp1252.py", line 23, in decode
        return codecs.charmap_decode(input,self.errors,decoding_table)[0]
    UnicodeDecodeError: 'charmap' codec can't decode byte 0x8f in position 21: character maps to <undefined>

    ----------------------------------------
Command "python setup.py egg_info" failed with error code 1 in C:\Users\Diksha\AppData\Local\Temp\pip-req-build-5ibodt8c\

please delete this queestion

Hi,

can we use intelMKL instead of openBlas ? its little bit faster than openblas

Best

Hi I am trying to use this but I ran into a problem that when I use 'python setup.py install ' in cmd and it shows finished successfully and I can import faced in my python. However when I try to use faced directly in cmd it cannot recognize it as an valid command. I am confused about that issue. I am very grateful if anyone can help me. Thx!

Hi, how can I solve problem faced is not recognized as an internal command?

Hello!

I'm trying to run faced, and use the code from the example. But it gives out a strange wrong result.
Does this software require image preprocessing before putting them to the input?

www.imgur.com/3XUoU3d

Hi!

Thank you for sharing this tool.
I was having this issue while running faced with an .mp4 video.

This is the terminal output:

Traceback (most recent call last):
  File "../bin/faced", line 143, in <module>
    run_video(path, t, args.save)
  File "../bin/faced", line 103, in run_video
    if frame.shape[0] == 0:
AttributeError: 'NoneType' object has no attribute 'shape'

The segment of the code that is pointing in faced is:

      ... 
      cap = cv2.VideoCapture(path)
       ...
       # Capture frame-by-frame
        ret, frame = cap.read()
        if frame.shape[0] == 0:
            break

Have you got any idea what can be happening here?
I am using a python3 conda enviroment, with tensorflow-gpu installed.

Thanks!

Hello good sir, I hope you are having a great day. I have this idea that I wish to share, any chance we can exchange emails? 😄

Mine is [email protected]. Cheers!

Hi all,

Great package - much faster than many of the other options.

I'm running into an issue where, for some images, the boxes are drawn in the incorrect place. The number of boxes is correct, it just looks as though the boxes have been shifted left. See an example below.

(The image is just a random photo from the internet. The original image is here)

I've been over the code and I cannot see why this would occur. I've also tried resizing the image, including changing the aspect ratio, and the result is the same. Has anyone had a similar experience?

Edit: To be clearer - it only occurs on some images, not all. So I don't think it's a problem with the install.

Faced is really awesome and light! Can you tell me how is dataset shape and structure? i would like to train my yolo into just 5 classs

Hi, thanks for this cpu real time face detect algorithm, is there any plan to open source training code?