I want to train different transfer learning model on emotion detection so that we get good accuracy and less loss.

Friend, I'm trainning the FER2013 like you, approximate answer like you, the acc will be around 95%, but val_acc remain around 60%. I search it on google, and others tell me that because overfitting.

why you have changed the sequence of emotions from {0:"Angry", 1:"Disgust", 2:"Fear", 3:"Happy", 4:"Sad", 5:"Surprise", 6:"Neutral"} to {0: "Angry", 1: "Disgusted", 2: "Fearful", 3: "Happy", 4: "Neutral", 5: "Sad", 6: "Surprised"} in emotions.py?

Dear mr Balaji,
I tried your project Emotion-detection. First I faced problem with the requirements, I solved it but then in the web camera i was smiling like crazy or opening mouth for surprised but it was always “Neutral”. How can i solve this?
Thanks in advance.
Regards,
P. Antonina

during training, it is showing this error:
File "C:\Users\lenovo\Anaconda3\envs\mypr\lib\site-packages\numpy\core_asarray.py", line 85, in asarray
return array(a, dtype, copy=False, order=order)
TypeError: float() argument must be a string or a number, not 'PngImageFile'

Hello,
Thanks for this work, I want to know how I can run this model in the C# or C++?
I want to integrate this repo with OpenFace.

Thanks in advance for any help

Hi

how can we change the frame size of video streaming.
please reach out to me at [email protected]

Found 28709 images belonging to 7 classes.
Found 7178 images belonging to 7 classes.

when iam running its just classifying dataset but webcam is not opening can you explain why is this happening?

Hello! First of all, thanks for your code, it's awesome. I wanna ask you how to train the model with another dataset, to make it better and get a better accuracy. For example, with CK + https://www.kaggle.com/shawon10/ckplus
or with FER2013+ https://github.com/microsoft/FERPlus
In the last case, how do you transform the .csv into png?
Regards,
Jaime!

Hi
I want to research Emotion detection using deep learning, I saw your project on github. But unfortunately I can not see the output. I am currently using spyder.
please guide me
Thanks
Askari

아이폰 SE

I am facing this error called "The system cannot find the path specified : 'data/train' ". Can you please let me know that should we have to first divide data into train and test then run this code ?

Update the kerasmodel.py data generator directory from
val_dir = 'data/val'
to
val_dir = 'data/test'

Buenas tardes! me parece excelente tu trabajo. Mil gracias por compartirlo, me ha servido mucho en mi trabajo de tesis para combatir el bullying. Podría conocer un poco más sobre los algoritmos?

My cuda version is 11.2 and cuDNN is 8.1

2024-02-23 14:22:42.333730: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2024-02-23 14:22:42.334621: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found
2024-02-23 14:22:42.335515: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found

Hi,

Nice and neat work, I want to know will the license be provided? preferably MIT license, because I could not find any LICENSE file in the repo..

Kind Regards

First of all, thanks for sharing your awesome work!

I am confused by this line: https://github.com/atulapra/Emotion-detection/blob/master/singleface.py#L68

Could you please share more insights on why you do this? Thanks again in advance!

I did everything in the readme and tried to run this in my command line but i keep getting this error

I'm getting this error when i run program with: python model.py singleface

File structure:

./
├── __pycache__/
│  ├── model.cpython-36.pyc
│  └── singleface.cpython-36.pyc
├── Data/
├── emojis/
│  ├── angry.png
│  ├── disgusted.png
│  ├── fearful.png
│  ├── happy.png
│  ├── neutral.png
│  ├── sad.png
│  └── surprised.png
├── Data.tar.gz
├── haarcascade_frontalface_default.xml
├── model.py
├── model_1_atul.tflearn.data-00000-of-00001
├── model_1_atul.tflearn.index
├── model_1_atul.tflearn.meta
├── multiface.py
└── singleface.py

Full Traceback:

------------Emotion Detection Program------------

Input data      (48, 48, 1)
WARNING:tensorflow:From /home/dentrax/Projects/GitHub/emotion-recognition-neural-networks/lib/python3.6/site-packages/tflearn/initializations.py:119: UniformUnitScaling.__init__ (from tensorflow.python.ops.init_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.initializers.variance_scaling instead with distribution=uniform to get equivalent behavior.
Conv1           (48, 48, 64)
Maxpool1        (24, 24, 64)
Conv2           (24, 24, 64)
Maxpool2        (12, 12, 64)
Conv3           (12, 12, 128)
Dropout         (12, 12, 128)
Fully connected (3072,)
Output          (7,)
WARNING:tensorflow:From /home/dentrax/Projects/GitHub/emotion-recognition-neural-networks/lib/python3.6/site-packages/tflearn/objectives.py:66: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
2019-01-20 22:18:54.042648: E tensorflow/stream_executor/cuda/cuda_driver.cc:300] failed call to cuInit: CUDA_ERROR_NO_DEVICE: no CUDA-capable device is detected
Traceback (most recent call last):
  File "model.py", line 75, in <module>
    import singleface
  File "/home/dentrax/Projects/GitHub/Emotion-detection/TFLearn/singleface.py", line 66, in <module>
    result = network.predict(format_image(frame))
  File "/home/dentrax/Projects/GitHub/Emotion-detection/TFLearn/singleface.py", line 22, in format_image
    faces = cascade_classifier.detectMultiScale(image,scaleFactor = 1.3 ,minNeighbors = 5)
NameError: name 'cascade_classifier' is not defined

Hi,

Thanks for sharing your awesome work. It works well in single face detection.

I saw that you are passing a gray image to model for single face detection and a color image to model for multi-face detection. When I passed gray image to model for multi-face, the detecion is great.

Please check.

Thanks,
Thomas.

Hello,
I want to use my own trained model for emotion detection (.h5 model), but I get the below error, could you let me know what is the problem?

2022-10-04 17:31:37.690958: I tensorflow/stream_executor/cuda/cudart_stub.cc:29] Ignore above cudart dlerror if you do not have a GPU set up on your machine.
Found 28709 images belonging to 7 classes.
Found 7178 images belonging to 7 classes.
2022-10-04 17:31:50.018247: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'nvcuda.dll'; dlerror: nvcuda.dll not found
2022-10-04 17:31:50.018462: W tensorflow/stream_executor/cuda/cuda_driver.cc:263] failed call to cuInit: UNKNOWN ERROR (303)
2022-10-04 17:31:50.024974: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:169] retrieving CUDA diagnostic information for host: DESKTOP-41NG8QC
2022-10-04 17:31:50.025176: I tensorflow/stream_executor/cuda/cuda_diagnostics.cc:176] hostname: DESKTOP-41NG8QC
2022-10-04 17:31:50.025657: I tensorflow/core/platform/cpu_feature_guard.cc:193] This TensorFlow binary is optimized with oneAPI Deep Neural Network Library (oneDNN) to use the following CPU instructions in performance-critical operations:  AVX AVX2
To enable them in other operations, rebuild TensorFlow with the appropriate compiler flags.```

I'm not sure how you even ran the code with this error.
File "emotions.py", line 98, in <module> plot_model_history(model_info) File "emotions.py", line 26, in plot_model_history axs[0].plot(range(1,len(model_history.history['acc'])+1),model_history.history['acc']) KeyError: 'acc'

You should replace all instances of 'accuracy' with 'acc', or vice versa.

After training for 50 epochs (3 hours), the program threw an error because you forgot
import matplotlib.pyplot as plt
Please add this to emotions.py.

It doesn't detect disgusted or fear face too. Also is there any method to improve the accuracy?

Hi, thanks for the code, and your trained model seems to work quite well!

I'm a bit of a beginner, and I'm working on a project where I'd need to obtain percentile probabilities of all emotions as opposed rounding them up to 1 and then displaying the highest probability.

What would be the best way to approach this? Thanks!

Hi, how can I import a random .jpg file?

how did you get graphs?
model accuracy and model loss

The single face with TFLearn is working perfectly, but both the muiface and the keras are giving the same error. It seems that it is not having the frame correctly as I put:

ret, frame = cap.read()
    if not ret:
        print("Could not read frame")
    else :

and it is continuously printing "Could not read frame". Has someone solve this? I am working reading a video so I changed cap = cv2.VideoCapture(0) to cap = cv2.VideoCapture('diner.mp4'), that's the only change I made

I used this code and model as it is.
but when i m going to test only 2 emotions are recongnizing.
and default it is showing happy without human face
pls solve this

When I execute the code 'python em_model.py singleface', it occurs this error. How can I solve this error???

(cv) pi@raspberrypi:~/Emotion-detection $ python em_model.py singleface
/home/pi/.virtualenvs/cv/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: compiletime version 3.4 of module 'tensorflow.python.framework.fast_tensor_util' does not match runtime version 3.5
return f(*args, **kwds)
/home/pi/.virtualenvs/cv/lib/python3.5/importlib/_bootstrap.py:222: RuntimeWarning: builtins.type size changed, may indicate binary incompatibility. Expected 432, got 412
return f(*args, **kwds)
/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/h5py/init.py:36: FutureWarning: Conversion of the second argument of issubdtype from float to np.floating is deprecated. In future, it will be treated as np.float64 == np.dtype(float).type.
from ._conv import register_converters as _register_converters

------------Emotion Detection Program------------

---> Starting Neural Network

Input data (48, 48, 1)
WARNING:tensorflow:From /home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/initializations.py:119: UniformUnitScaling.init (from tensorflow.python.ops.init_ops) is deprecated and will be removed in a future version.
Instructions for updating:
Use tf.initializers.variance_scaling instead with distribution=uniform to get equivalent behavior.
Conv1 (48, 48, 64)
Maxpool (24, 24, 64)
Conv2 (24, 24, 64)
Maxpool2 (12, 12, 64)
Conv3 (12, 12, 128)
Dropout (12, 12, 128)
Fully connected (3072,)
Output (4,)

WARNING:tensorflow:From /home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/objectives.py:66: calling reduce_sum (from tensorflow.python.ops.math_ops) with keep_dims is deprecated and will be removed in a future version.
Instructions for updating:
keep_dims is deprecated, use keepdims instead
2018-10-20 00:00:06.073932: W tensorflow/core/framework/allocator.cc:113] Allocation of 12288 exceeds 10% of system memory.
2018-10-20 00:00:06.098093: W tensorflow/core/framework/allocator.cc:113] Allocation of 6400 exceeds 10% of system memory.
2018-10-20 00:00:06.105248: W tensorflow/core/framework/allocator.cc:113] Allocation of 409600 exceeds 10% of system memory.
2018-10-20 00:00:06.108324: W tensorflow/core/framework/allocator.cc:113] Allocation of 524288 exceeds 10% of system memory.
2018-10-20 00:00:06.111486: W tensorflow/core/framework/allocator.cc:113] Allocation of 226492416 exceeds 10% of system memory.
Traceback (most recent call last):
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1292, in _do_call
return fn(*args)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1277, in _run_fn
options, feed_dict, fetch_list, target_list, run_metadata)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1367, in _call_tf_sessionrun
run_metadata)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [4] rhs shape= [7]
[[{{node save_1/Assign_21}} = Assign[T=DT_FLOAT, _class=["loc:@FullyConnected_1/b"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](FullyConnected_1/b/Momentum, save_1/RestoreV2:21)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1538, in restore
{self.saver_def.filename_tensor_name: save_path})
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 887, in run
run_metadata_ptr)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1110, in _run
feed_dict_tensor, options, run_metadata)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1286, in _do_run
run_metadata)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/client/session.py", line 1308, in _do_call
raise type(e)(node_def, op, message)
tensorflow.python.framework.errors_impl.InvalidArgumentError: Assign requires shapes of both tensors to match. lhs shape= [4] rhs shape= [7]
[[{{node save_1/Assign_21}} = Assign[T=DT_FLOAT, _class=["loc:@FullyConnected_1/b"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](FullyConnected_1/b/Momentum, save_1/RestoreV2:21)]]

Caused by op 'save_1/Assign_21', defined at:
File "em_model.py", line 77, in
import singleface
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 673, in _load_unlocked
File "", line 673, in exec_module
File "", line 222, in _call_with_frames_removed
File "/home/pi/Emotion-detection/singleface.py", line 48, in
network.build_network()
File "/home/pi/Emotion-detection/em_model.py", line 50, in build_network
self.model = tflearn.DNN(self.network,checkpoint_path = 'model_1_atul',max_checkpoints = 1,tensorboard_verbose = 2)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/models/dnn.py", line 65, in init
best_val_accuracy=best_val_accuracy)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/helpers/trainer.py", line 147, in init
allow_empty=True)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1094, in init
self.build()
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1106, in build
self._build(self._filename, build_save=True, build_restore=True)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1143, in _build
build_save=build_save, build_restore=build_restore)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 787, in _build_internal
restore_sequentially, reshape)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 428, in _AddRestoreOps
assign_ops.append(saveable.restore(saveable_tensors, shapes))
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 119, in restore
self.op.get_shape().is_fully_defined())
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/ops/state_ops.py", line 221, in assign
validate_shape=validate_shape)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/ops/gen_state_ops.py", line 61, in assign
use_locking=use_locking, name=name)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3272, in create_op
op_def=op_def)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1768, in init
self._traceback = tf_stack.extract_stack()

InvalidArgumentError (see above for traceback): Assign requires shapes of both tensors to match. lhs shape= [4] rhs shape= [7]
[[{{node save_1/Assign_21}} = Assign[T=DT_FLOAT, _class=["loc:@FullyConnected_1/b"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](FullyConnected_1/b/Momentum, save_1/RestoreV2:21)]]

During handling of the above exception, another exception occurred:

Traceback (most recent call last):
File "em_model.py", line 77, in
import singleface
File "/home/pi/Emotion-detection/singleface.py", line 48, in
network.build_network()
File "/home/pi/Emotion-detection/em_model.py", line 52, in build_network
self.load_model()
File "/home/pi/Emotion-detection/em_model.py", line 68, in load_model
self.model.load("model_1_atul.tflearn")
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/models/dnn.py", line 308, in load
self.trainer.restore(model_file, weights_only, **optargs)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/helpers/trainer.py", line 490, in restore
self.restorer.restore(self.session, model_file)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1574, in restore
err, "a mismatch between the current graph and the graph")
tensorflow.python.framework.errors_impl.InvalidArgumentError: Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Assign requires shapes of both tensors to match. lhs shape= [4] rhs shape= [7]
[[{{node save_1/Assign_21}} = Assign[T=DT_FLOAT, _class=["loc:@FullyConnected_1/b"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](FullyConnected_1/b/Momentum, save_1/RestoreV2:21)]]

Caused by op 'save_1/Assign_21', defined at:
File "em_model.py", line 77, in
import singleface
File "", line 969, in _find_and_load
File "", line 958, in _find_and_load_unlocked
File "", line 673, in _load_unlocked
File "", line 673, in exec_module
File "", line 222, in _call_with_frames_removed
File "/home/pi/Emotion-detection/singleface.py", line 48, in
network.build_network()
File "/home/pi/Emotion-detection/em_model.py", line 50, in build_network
self.model = tflearn.DNN(self.network,checkpoint_path = 'model_1_atul',max_checkpoints = 1,tensorboard_verbose = 2)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/models/dnn.py", line 65, in init
best_val_accuracy=best_val_accuracy)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tflearn/helpers/trainer.py", line 147, in init
allow_empty=True)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1094, in init
self.build()
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1106, in build
self._build(self._filename, build_save=True, build_restore=True)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 1143, in _build
build_save=build_save, build_restore=build_restore)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 787, in _build_internal
restore_sequentially, reshape)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 428, in _AddRestoreOps
assign_ops.append(saveable.restore(saveable_tensors, shapes))
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/training/saver.py", line 119, in restore
self.op.get_shape().is_fully_defined())
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/ops/state_ops.py", line 221, in assign
validate_shape=validate_shape)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/ops/gen_state_ops.py", line 61, in assign
use_locking=use_locking, name=name)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/framework/op_def_library.py", line 787, in _apply_op_helper
op_def=op_def)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/util/deprecation.py", line 488, in new_func
return func(*args, **kwargs)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 3272, in create_op
op_def=op_def)
File "/home/pi/.virtualenvs/cv/local/lib/python3.5/site-packages/tensorflow/python/framework/ops.py", line 1768, in init
self._traceback = tf_stack.extract_stack()

InvalidArgumentError (see above for traceback): Restoring from checkpoint failed. This is most likely due to a mismatch between the current graph and the graph from the checkpoint. Please ensure that you have not altered the graph expected based on the checkpoint. Original error:

Assign requires shapes of both tensors to match. lhs shape= [4] rhs shape= [7]
[[{{node save_1/Assign_21}} = Assign[T=DT_FLOAT, _class=["loc:@FullyConnected_1/b"], use_locking=true, validate_shape=true, _device="/job:localhost/replica:0/task:0/device:CPU:0"](FullyConnected_1/b/Momentum, save_1/RestoreV2:21)]]

On running this line python emotions.py --mode train, I'm getting this error: The system cannot find the path specified: 'data/train'. Please help as I'm new to data science.

Hi, thanks for your sharing. When I used python em_model.py singleface , the screen is always one emotion, the result is all like this:
...
[0 0 0 ... 0 0 0]
[0 0 0 ... 0 0 0]
[0 0 0 ... 0 0 0]]
[[0 0 0 ... 0 0 0]
[0 0 0 ... 0 0 0]
[0 0 0 ... 0 0 0]

I think that the project isn't loaded model. But I have placed the DATA in the Emotion-detection-master, and run it as you. Please help me about this question. I don't know why the model isn't run. Thank you very much!

Hi
When I execute the code 'python emotions.py --mode train',
after 50/50 epoches, it occurs this error, can't generate new training files. How can I solve this error???

full error:
Traceback (most recent call last):
File "emotions.py", line 98, in
plot_model_history(model_info)
File "emotions.py", line 31, in plot_model_history
axs[0].set_xticks(np.arange(1,len(model_history.history['accuracy'])+1),len(model_history.history['accuracy'])/10)
File "/home/jaeger/.local/lib/python3.8/site-packages/matplotlib/axes/_base.py", line 75, in wrapper
return get_method(self)(*args, **kwargs)
File "/home/jaeger/.local/lib/python3.8/site-packages/matplotlib/axis.py", line 1857, in set_ticks
self.set_ticklabels(labels, minor=minor, **kwargs)
File "/home/jaeger/.local/lib/python3.8/site-packages/matplotlib/axis.py", line 1712, in set_ticklabels
ticklabels = [t.get_text() if hasattr(t, 'get_text') else t
TypeError: 'float' object is not iterable

thanks.

Lovely work! Do you remember at what epoch did you get your pre-trained model from? Or what was the val_loss/acc of your pre-trained model that you made available?

The following code leads to errors:

from em_model import EMR  
n1 = EMR()    
n1.build_network()  
n2 = EMR()  
n2.build_network()

The solution is importing tensorflow and resetting default graph at the first of build_network:

tf.reset_default_graph()

Getting this error when I try to train

Traceback (most recent call last):
File "emotions.py", line 98, in
plot_model_history(model_info)
File "emotions.py", line 31, in plot_model_history
axs[0].set_xticks(np.arange(1,len(model_history.history['accuracy'])+1),len(model_history.history['accuracy'])/10)
File "/home/touseef/.local/lib/python3.8/site-packages/matplotlib/axes/_base.py", line 73, in wrapper
return get_method(self)(*args, **kwargs)
TypeError: set_ticks() takes 2 positional arguments but 3 were given

model.h5 file is missing

Full error:
File "emotions.py", line 97, in
validation_steps=num_val // batch_size)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py", line 1957, in fit_generator
initial_epoch=initial_epoch)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/training.py", line 1147, in fit
steps_per_execution=self._steps_per_execution)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 1364, in get_data_handler
return DataHandler(*args, **kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 1166, in init
model=model)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 939, in init
**kwargs)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 809, in init
peek, x = self._peek_and_restore(x)
File "/usr/local/lib/python3.6/dist-packages/tensorflow/python/keras/engine/data_adapter.py", line 943, in _peek_and_restore
return x[0], x
File "/usr/local/lib/python3.6/dist-packages/keras_preprocessing/image/iterator.py", line 57, in getitem
length=len(self)))
ValueError: Asked to retrieve element 0, but the Sequence has length 0

is this need GPU?
I had run it on my computer by CPU. it's running so slowly, so jam.

and I can run kargle's py document,but I can't run TF-single document.because:
"cv2.error: OpenCV(3.4.2) /Users/travis/build/skvark/opencv-python/opencv/modules/objdetect/src/cascadedetect.cpp:1698: error: (-215:Assertion failed) !empty() in function 'detectMultiScale'"

so I tape 'pip install OpenCV-python==3.4.1 ' in terminal , but it show back this :

ERROR: Could not find a version that satisfies the requirement opencv-python==3.4.1 (from versions: 3.4.2.16, 3.4.2.17, 3.4.3.18, 3.4.4.19, 3.4.5.20, 3.4.6.27, 3.4.7.28, 4.0.0.21, 4.0.1.24, 4.1.0.25, 4.1.1.26)
ERROR: No matching distribution found for opencv-python==3.4.1

emmm...... so hurt

I get this when I run python3 model.py singleface
Traceback (most recent call last): File "model.py", line 3, in <module> import tflearn File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tflearn/__init__.py", line 4, in <module> from . import config File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tflearn/config.py", line 5, in <module> from .variables import variable File "/Library/Frameworks/Python.framework/Versions/3.7/lib/python3.7/site-packages/tflearn/variables.py", line 7, in <module> from tensorflow.contrib.framework.python.ops import add_arg_scope as contrib_add_arg_scope ModuleNotFoundError: No module named 'tensorflow.contrib'
I'm running MacOS High Sierra