deepface ResourceExhaustedError: failed to allocate memory [Op:AddV2]

Question

I am new to deeplearning. I am trying to use the deepface library in my local machine . I used pip install deepface to install the library, tried on python 3.7.13, 3.8.13 and 3.9.13 which were all created using conda virtual environment.

However when running the code snippet below, I am getting the same error when running on my local machine. Do I need a GPU to run the library? If yes, how do I set it up? Because from the online guides/ articles, none of them mentioned the need of installing / setup a GPU.

I have a GeForce MX450 on my local pc.

code

import cv2
from deepface import DeepFace
import numpy as np

def analyse_face():
    imagepath = "happy_face_woman.png"
    image = cv2.imread(imagepath)
    face_analysis = DeepFace.analyze(image)
    print(face_analysis)

print(analyse_face())

Error:

ResourceExhaustedError                    Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_14196\3829791526.py in <module>
     12     print(face_analysis)
     13 
---> 14 analyse_face()

~\AppData\Local\Temp\ipykernel_14196\3829791526.py in analyse_face()
      9     imagepath = "happy_face_woman.png"
     10     image = cv2.imread(imagepath)
---> 11     face_analysis = DeepFace.analyze(image)
     12     print(face_analysis)
     13 

c:\Users\user_name\anaconda3\envs\deepFacepy37\lib\site-packages\deepface\DeepFace.py in analyze(img_path, actions, models, enforce_detection, detector_backend, prog_bar)
    352 
    353         if 'age' in actions and 'age' not in built_models:
--> 354                 models['age'] = build_model('Age')
    355 
    356         if 'gender' in actions and 'gender' not in built_models:

c:\Users\user_name\anaconda3\envs\deepFacepy37\lib\site-packages\deepface\DeepFace.py in build_model(model_name)
     61                 model = models.get(model_name)
     62                 if model:
---> 63                         model = model()
...
-> 1922         seed=self.make_legacy_seed())
   1923 
   1924   def truncated_normal(self, shape, mean=0., stddev=1., dtype=None):

ResourceExhaustedError: failed to allocate memory [Op:AddV2]

Different Error output

ResourceExhaustedError                    Traceback (most recent call last)
~\AppData\Local\Temp\ipykernel_14196\3829791526.py in <module>
     12     print(face_analysis)
     13 
---> 14 analyse_face()

~\AppData\Local\Temp\ipykernel_14196\3829791526.py in analyse_face()
      9     imagepath = "happy_face_woman.png"
     10     image = cv2.imread(imagepath)
---> 11     face_analysis = DeepFace.analyze(image)
     12     print(face_analysis)
     13 

c:\Users\user_name\anaconda3\envs\deepFacepy37\lib\site-packages\deepface\DeepFace.py in analyze(img_path, actions, models, enforce_detection, detector_backend, prog_bar)
    352 
    353         if 'age' in actions and 'age' not in built_models:
--> 354                 models['age'] = build_model('Age')
    355 
    356         if 'gender' in actions and 'gender' not in built_models:

c:\Users\user_name\anaconda3\envs\deepFacepy37\lib\site-packages\deepface\DeepFace.py in build_model(model_name)
     61                 model = models.get(model_name)
     62                 if model:
---> 63                         model = model()
...
-> 1922         seed=self.make_legacy_seed())
   1923 
   1924   def truncated_normal(self, shape, mean=0., stddev=1., dtype=None):

ResourceExhaustedError: OOM when allocating tensor with shape[7,7,512,4096] and type float on /job:localhost/replica:0/task:0/device:GPU:0 by allocator GPU_0_bfc [Op:RandomUniform]

Additional Info I've ran the command to check my GPU usage and the details is as follows:

!nvidia-smi

Answer 1

Why do not you disable GPU?

import os
os.environ["CUDA_VISIBLE_DEVICES"]=""