Real-time face detection and emotion/gender classification using fer2013/imdb datasets with a keras CNN model and openCV.

Related tags

Deep Learning face_classification
Overview

This repository is deprecated for at TF-2.0 rewrite visit:

https://github.com/oarriaga/paz

Face classification and detection.

Real-time face detection and emotion/gender classification using fer2013/IMDB datasets with a keras CNN model and openCV.

  • IMDB gender classification test accuracy: 96%.
  • fer2013 emotion classification test accuracy: 66%.

For more information please consult the publication

Emotion/gender examples:

alt tag

Guided back-prop alt tag

Real-time demo:

B-IT-BOTS robotics team :) alt tag

Instructions

Run real-time emotion demo:

python3 video_emotion_color_demo.py

Run real-time guided back-prop demo:

python3 image_gradcam_demo.py

Make inference on single images:

python3 image_emotion_gender_demo.py

e.g.

python3 image_emotion_gender_demo.py ../images/test_image.jpg

Running with Docker

With a few steps one can get its own face classification and detection running. Follow the commands below:

  • docker pull ekholabs/face-classifier
  • docker run -d -p 8084:8084 --name=face-classifier ekholabs/face-classifier
  • curl -v -F image=@[path_to_image] http://localhost:8084/classifyImage > image.png

To train previous/new models for emotion classification:

  • Download the fer2013.tar.gz file from here

  • Move the downloaded file to the datasets directory inside this repository.

  • Untar the file:

tar -xzf fer2013.tar

  • Run the train_emotion_classification.py file

python3 train_emotion_classifier.py

To train previous/new models for gender classification:

  • Download the imdb_crop.tar file from here (It's the 7GB button with the tittle Download faces only).

  • Move the downloaded file to the datasets directory inside this repository.

  • Untar the file:

tar -xfv imdb_crop.tar

  • Run the train_gender_classification.py file

python3 train_gender_classifier.py

Comments
  • Dockerize the project and add a RESTful service to process images

    Dockerize the project and add a RESTful service to process images

    This pull request extends the current code base to add Docker compliance and a RESTful service that can be used to process images without having to execute Python locally.

    All the dependencies are covered with the Docker file that has been added. It requires only one command line to get an image to be processed.

    I hope you like this addition to the project.

    Cheers, Wilder

    opened by wilderrodrigues 11
  • problem with runs code in other platform

    problem with runs code in other platform

    hello orriaga...codes works so great for me in ubuntu os... when i run video_emotion_gender_demo in raspberry pi that have raspbian stretch as os ,then i got some errors ,did you know i how overcome the errors thanks in advance

    opened by fadsamo 8
  • Incompatible optimizer weight

    Incompatible optimizer weight

    Newest commit fires the following error

      File "C:/face_classification-master/face_classification-master/src/video_emotion_color_demo.py", line 26, in <module>
    emotion_classifier = load_model(emotion_model_path, custom_objects=False)
  File "C:\ProgramData\Anaconda3\lib\site-packages\keras\models.py", line 272, in load_model
    model.optimizer.set_weights(optimizer_weight_values)
  File "C:\ProgramData\Anaconda3\lib\site-packages\keras\optimizers.py", line 79, in set_weights
    'provided weight shape ' + str(w.shape))
ValueError: Optimizer weight shape (8,) not compatible with provided weight shape (64,)
    opened by Zumbalamambo 8
  • How to retrain the model?

    How to retrain the model?

    Hello,

    I have been facing trouble when I try to retrain the train_emotion_classifier model. The model don't finish all 1000 but stop ones at epoch 00156 and the second time at epoch 00136.

    Can you please explain me the reason? Thanks for your help

    opened by MariemSlim 6
  • feature request - python2.7 support

    feature request - python2.7 support

    is python3 strictly required for this? I ran the demo with python2.7 , no errors but no output. The net seems to load but nothing more.

    jeremy@jr:~/projects/face_classification/src$ python image_emotion_gender_demo.py ../images/test_image.jpg 
Using TensorFlow backend.
...
2017-11-02 09:09:55.707876: W tensorflow/core/platform/cpu_feature_guard.cc:45] The TensorFlow library wasn't compiled to use FMA instructions, but these are available on your machine and could speed up CPU computations.
jeremy@jr:~/projects/face_classification/src$
    opened by jeremy-rutman 5
  • Using new training model

    Using new training model

    Hello, first of all the code is great! The problem is that I'm trying training new models, and when I put one model in the code instead of the "simple CNN" one, it throws an error of the input shape. What can I do?

    ValueError: Error when checking : expected input_1 to have shape (None, 64, 64, 1) but got array with shape (1, 64, 64, 3)

    opened by tombauz 4
  • save detected result and video file as a input

    save detected result and video file as a input

    Hi @oarriaga ,

    I am wondering is there a way, by which we can save the detected result e.g. emotion detected after running the script video_emotion_color_demo.py . Also can we run this script on video files (mp4) saved on local system for emotion detection or gender classification ? If yes can you modify the code or tell me how to do it ?

    opened by trohit920 4
  • can not run vdeo_emotion_color_demo.py

    can not run vdeo_emotion_color_demo.py

    Hi, I can not start your project. TF, Keras, OpenCV and other libs installed What i do source ./tensorflow/bin/activate //activate TF (tensorflow) gubiniliya@Lenovo-Z50-75:~/Documents/face_classification-master/src$ python3 video_emotion_color_demo.py And i have an error

    
Using TensorFlow backend.
/home/gubiniliya/Documents/face_classification-master/src/tensorflow/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6
  return f(*args, **kwds)
2017-11-30 11:15:39.289068: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX FMA
OpenCV Error: Assertion failed (scn == 3 || scn == 4) in cvtColor, file /io/opencv/modules/imgproc/src/color.cpp, line 10638
Traceback (most recent call last):
  File "video_emotion_color_demo.py", line 39, in <module>
    gray_image = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2GRAY)
cv2.error: /io/opencv/modules/imgproc/src/color.cpp:10638: error: (-215) scn == 3 || scn == 4 in function cvtColor

    Okay, i see on line 39 =) Yep gray_image = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2GRAY) rgb_image = cv2.cvtColor(bgr_image, cv2.COLOR_BGR2RGB) and i found this issue on stackoverflow there they advised us to write the full path to the picture, but we also get video from the camera bgr_image = video_capture.read()[1] ok, for test i change bgr_image to "/home/gubiniliya/Images/image.jpg" And where i do it i have a new error

    (tensorflow) gubiniliya@Lenovo-Z50-75:~/Documents/face_classification-master/src$ python3 video_emotion_color_demo.py
Using TensorFlow backend.
/home/gubiniliya/Documents/face_classification-master/src/tensorflow/lib/python3.6/importlib/_bootstrap.py:219: RuntimeWarning: compiletime version 3.5 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.6
  return f(*args, **kwds)
2017-11-30 11:28:17.264266: I tensorflow/core/platform/cpu_feature_guard.cc:137] Your CPU supports instructions that this TensorFlow binary was not compiled to use: SSE4.1 SSE4.2 AVX FMA
Traceback (most recent call last):
  File "video_emotion_color_demo.py", line 39, in <module>
    gray_image = cv2.cvtColor("/home/gubiniliya/Images/image.jpg", cv2.COLOR_BGR2GRAY)
TypeError: src is not a numpy array, neither a scalar

    What i need to do, for fix my problem and run projectwith cam

    opened by gubiniliya 4
  • Improve accuracy for emotion recognition module

    Improve accuracy for emotion recognition module

    The work done in the repo, is outstanding, and the reults are pretty good as well,, it's accuracy is much more than what you have mentioned in README,, I guess it's arround 78% or more,, but am really interested to know how I can contribute to improve the overall accuracy of the project, so will changing the dataset affect more or by using some other CNN module parameters will work, or instead can we make use of caffe module directly instead of tensorflow as backend,, so let me know, it will be fun to contribute this repo.

    Thanks & Regards, Swap

    opened by andro-galexy 4
  • The Strategy of facial expression recogition

    The Strategy of facial expression recogition

    Hi , It's a pleasure to see such good open source code。 in face, i am also doing the research of facial expression recognition . i want to know what effective skills have you taken. i see the CNN structure is ordinary except depth. and what's the effect when the real test is done.

    opened by zhanglaplace 4
  • A problem when running

    A problem when running "image_gradcam_demo.py"

    Traceback (most recent call last): File "image_gradcam_demo.py", line 73, in predicted_class, 'conv2d_7') File "/home/zengyiqi/project/face_classification/src/utils/grad_cam.py", line 115, in compile_gradient_function gradients = normalize(K.gradients(loss, conv_output)[0]) File "/home/zengyiqi/project/face_classification/src/utils/grad_cam.py", line 31, in normalize return x / (K.sqrt(K.mean(K.square(x))) + 1e-5) File "/home/zengyiqi/anaconda2/lib/python2.7/site-packages/keras/backend/tensorflow_backend.py", line 1417, in square return tf.square(x) File "/home/zengyiqi/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/math_ops.py", line 449, in square return gen_math_ops.square(x, name=name) File "/home/zengyiqi/anaconda2/lib/python2.7/site-packages/tensorflow/python/ops/gen_math_ops.py", line 4567, in square "Square", x=x, name=name) File "/home/zengyiqi/anaconda2/lib/python2.7/site-packages/tensorflow/python/framework/op_def_library.py", line 528, in _apply_op_helper (input_name, err)) ValueError: Tried to convert 'x' to a tensor and failed. Error: None values not supported.

    when I ran the commad of "python image_gradcam_demo.py ../images/test_image.jpg"， there is a problem with the errer log above. How can I solve this problem? I would appreciate it very much if you could help me！

    opened by ustczeng 3
  • Bump tensorflow from 1.1.0 to 2.9.3

    Bump tensorflow from 1.1.0 to 2.9.3

    Bumps tensorflow from 1.1.0 to 2.9.3.

    Release notes

    Sourced from tensorflow's releases.

    TensorFlow 2.9.3

    Release 2.9.3

    This release introduces several vulnerability fixes:

    TensorFlow 2.9.2

    Release 2.9.2

    This releases introduces several vulnerability fixes:

    ... (truncated)

    Changelog

    Sourced from tensorflow's changelog.

    Release 2.9.3

    This release introduces several vulnerability fixes:

    Release 2.8.4

    This release introduces several vulnerability fixes:

    ... (truncated)

    Commits
    • a5ed5f3 Merge pull request #58584 from tensorflow/vinila21-patch-2
    • 258f9a1 Update py_func.cc
    • cd27cfb Merge pull request #58580 from tensorflow-jenkins/version-numbers-2.9.3-24474
    • 3e75385 Update version numbers to 2.9.3
    • bc72c39 Merge pull request #58482 from tensorflow-jenkins/relnotes-2.9.3-25695
    • 3506c90 Update RELEASE.md
    • 8dcb48e Update RELEASE.md
    • 4f34ec8 Merge pull request #58576 from pak-laura/c2.99f03a9d3bafe902c1e6beb105b2f2417...
    • 6fc67e4 Replace CHECK with returning an InternalError on failing to create python tuple
    • 5dbe90a Merge pull request #58570 from tensorflow/r2.9-7b174a0f2e4
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    dependencies 
    opened by dependabot[bot] 0
  • Bump numpy from 1.12.1 to 1.22.0

    Bump numpy from 1.12.1 to 1.22.0

    Bumps numpy from 1.12.1 to 1.22.0.

    Release notes

    Sourced from numpy's releases.

    v1.22.0

    NumPy 1.22.0 Release Notes

    NumPy 1.22.0 is a big release featuring the work of 153 contributors spread over 609 pull requests. There have been many improvements, highlights are:

    • Annotations of the main namespace are essentially complete. Upstream is a moving target, so there will likely be further improvements, but the major work is done. This is probably the most user visible enhancement in this release.
    • A preliminary version of the proposed Array-API is provided. This is a step in creating a standard collection of functions that can be used across application such as CuPy and JAX.
    • NumPy now has a DLPack backend. DLPack provides a common interchange format for array (tensor) data.
    • New methods for quantile, percentile, and related functions. The new methods provide a complete set of the methods commonly found in the literature.
    • A new configurable allocator for use by downstream projects.

    These are in addition to the ongoing work to provide SIMD support for commonly used functions, improvements to F2PY, and better documentation.

    The Python versions supported in this release are 3.8-3.10, Python 3.7 has been dropped. Note that 32 bit wheels are only provided for Python 3.8 and 3.9 on Windows, all other wheels are 64 bits on account of Ubuntu, Fedora, and other Linux distributions dropping 32 bit support. All 64 bit wheels are also linked with 64 bit integer OpenBLAS, which should fix the occasional problems encountered by folks using truly huge arrays.

    Expired deprecations

    Deprecated numeric style dtype strings have been removed

    Using the strings "Bytes0", "Datetime64", "Str0", "Uint32", and "Uint64" as a dtype will now raise a TypeError.

    (gh-19539)

    Expired deprecations for loads, ndfromtxt, and mafromtxt in npyio

    numpy.loads was deprecated in v1.15, with the recommendation that users use pickle.loads instead. ndfromtxt and mafromtxt were both deprecated in v1.17 - users should use numpy.genfromtxt instead with the appropriate value for the usemask parameter.

    (gh-19615)

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 0
  • which result from the prediction represents which emotion

    which result from the prediction represents which emotion

    i have been using this model  to classify emotions in my web app through tensorflowjs. I need some assistance , while using this model the results from the predictions are like these         

    [     
      2.1150742268716272e-10,
      1.902112662099779e-26,
      1,
      1.32382716176611e-30,
      2.0226073905495974e-27,
      1.619873832843048e-35,
      0
    ]

    what i cant understand is while array index represents which emotion between happy,disgust,fear,angry,sad,surprise,neutral. 

    opened by Heracraft 0
  • Bump opencv-python from 3.2.0 to 4.2.0.32

    Bump opencv-python from 3.2.0 to 4.2.0.32

    Bumps opencv-python from 3.2.0 to 4.2.0.32.

    Release notes

    Sourced from opencv-python's releases.

    4.2.0.32

    OpenCV version 4.2.0.

    Changes:

    • macOS environment updated from xcode8.3 to xcode 9.4
    • macOS uses now Qt 5 instead of Qt 4
    • Nasm version updated to Docker containers
    • multibuild updated

    Fixes:

    • don't use deprecated brew tap-pin, instead refer to the full package name when installing #267
    • replace get_config_var() with get_config_vars() in setup.py #274
    • add workaround for DLL errors in Windows Server #264

    3.4.9.31

    OpenCV version 3.4.9.

    Changes:

    • macOS environment updated from xcode8.3 to xcode 9.4
    • macOS uses now Qt 5 instead of Qt 4
    • Nasm version updated to Docker containers
    • multibuild updated

    Fixes:

    • don't use deprecated brew tap-pin, instead refer to the full package name when installing #267
    • replace get_config_var() with get_config_vars() in setup.py #274
    • add workaround for DLL errors in Windows Server #264

    4.1.2.30

    OpenCV version 4.1.2.

    Changes:

    ... (truncated)

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    dependencies 
    opened by dependabot[bot] 0
Owner
Octavio Arriaga
B.Sc. Physics, M.Sc. in Intelligent Robotics (Computer Vision, Deep Learning, NLP)
Octavio Arriaga
GitHub
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