How to solve error while importing pickle file?

Question

I am trying to make a traffic sign classification code with following this tutorial. I can trained model but when I tried to import pickle file(trined model) to this code ı got an error at model=pickle.load(hel) (line 21) how can I solve that?

Note: I installed tensorflow and pickle.

Console Messages

2022-03-19 11:53:44.525832: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-03-19 11:53:44.533297: 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.
2022-03-19 11:53:54.072135: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudart64_110.dll'; dlerror: cudart64_110.dll not found
2022-03-19 11:53:54.084145: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublas64_11.dll'; dlerror: cublas64_11.dll not found
2022-03-19 11:53:54.099108: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cublasLt64_11.dll'; dlerror: cublasLt64_11.dll not found
2022-03-19 11:53:54.110572: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cufft64_10.dll'; dlerror: cufft64_10.dll not found
2022-03-19 11:53:54.120208: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'curand64_10.dll'; dlerror: curand64_10.dll not found
2022-03-19 11:53:54.130490: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusolver64_11.dll'; dlerror: cusolver64_11.dll not found
2022-03-19 11:53:54.140943: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cusparse64_11.dll'; dlerror: cusparse64_11.dll not found
2022-03-19 11:53:54.150708: W tensorflow/stream_executor/platform/default/dso_loader.cc:64] Could not load dynamic library 'cudnn64_8.dll'; dlerror: cudnn64_8.dll not found
2022-03-19 11:53:54.157514: W tensorflow/core/common_runtime/gpu/gpu_device.cc:1850] Cannot dlopen some GPU libraries. Please make sure the missing libraries mentioned above are installed properly if you would like to use GPU. Follow the guide at https://www.tensorflow.org/install/gpu for how to download and setup the required libraries for your platform.
Skipping registering GPU devices...
2022-03-19 11:53:54.175013: I tensorflow/core/platform/cpu_feature_guard.cc:151] 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.

Error Message

Code:

import numpy as np
import cv2
import pickle
 
frameWidth= 640        
frameHeight = 480
brightness = 180
threshold = 0.90       
font = cv2.FONT_HERSHEY_SIMPLEX


cap = cv2.VideoCapture(0)
cap.set(3, frameWidth)
cap.set(4, frameHeight)
cap.set(10, brightness)
# IMPORT THE TRANNIED MODEL
hel=open("model_trained.p","rb")  ## rb = READ BYTE
model=pickle.load(hel)
 
def grayscale(img):
    img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)
    return img
def equalize(img):
    img =cv2.equalizeHist(img)
    return img
def preprocessing(img):
    img = grayscale(img)
    img = equalize(img)
    img = img/255
    return img
def getCalssName(classNo):
    if   classNo == 0: return 'Speed Limit 20 km/h'
    elif classNo == 1: return 'Speed Limit 30 km/h'
    elif classNo == 2: return 'Speed Limit 50 km/h'
    elif classNo == 3: return 'Speed Limit 60 km/h'
    elif classNo == 4: return 'Speed Limit 70 km/h'
    elif classNo == 5: return 'Speed Limit 80 km/h'
    elif classNo == 6: return 'End of Speed Limit 80 km/h'
    elif classNo == 7: return 'Speed Limit 100 km/h'
    elif classNo == 8: return 'Speed Limit 120 km/h'
    elif classNo == 9: return 'No passing'
    elif classNo == 10: return 'No passing for vechiles over 3.5 metric tons'
    elif classNo == 11: return 'Right-of-way at the next intersection'
    elif classNo == 12: return 'Priority road'
    elif classNo == 13: return 'Yield'
    elif classNo == 14: return 'Stop'
    elif classNo == 15: return 'No vechiles'
    elif classNo == 16: return 'Vechiles over 3.5 metric tons prohibited'
    elif classNo == 17: return 'No entry'
    elif classNo == 18: return 'General caution'
    elif classNo == 19: return 'Dangerous curve to the left'
    elif classNo == 20: return 'Dangerous curve to the right'
    elif classNo == 21: return 'Double curve'
    elif classNo == 22: return 'Bumpy road'
    elif classNo == 23: return 'Slippery road'
    elif classNo == 24: return 'Road narrows on the right'
    elif classNo == 25: return 'Road work'
    elif classNo == 26: return 'Traffic signals'
    elif classNo == 27: return 'Pedestrians'
    elif classNo == 28: return 'Children crossing'
    elif classNo == 29: return 'Bicycles crossing'
    elif classNo == 30: return 'Beware of ice/snow'
    elif classNo == 31: return 'Wild animals crossing'
    elif classNo == 32: return 'End of all speed and passing limits'
    elif classNo == 33: return 'Turn right ahead'
    elif classNo == 34: return 'Turn left ahead'
    elif classNo == 35: return 'Ahead only'
    elif classNo == 36: return 'Go straight or right'
    elif classNo == 37: return 'Go straight or left'
    elif classNo == 38: return 'Keep right'
    elif classNo == 39: return 'Keep left'
    elif classNo == 40: return 'Roundabout mandatory'
    elif classNo == 41: return 'End of no passing'
    elif classNo == 42: return 'End of no passing by vechiles over 3.5 metric tons'
 
while True:
    success, imgOrignal = cap.read()
 

    img = np.asarray(imgOrignal)
    img = cv2.resize(img, (32, 32))
    img = preprocessing(img)
    cv2.imshow("Processed Image", img)
    img = img.reshape(1, 32, 32, 1)
    cv2.putText(imgOrignal, "CLASS: " , (20, 35), font, 0.75, (0, 0, 255), 2, cv2.LINE_AA)
    cv2.putText(imgOrignal, "PROBABILITY: ", (20, 75), font, 0.75, (0, 0, 255), 2, cv2.LINE_AA)



    predictions = model.predict(img)
    classIndex = model.predict_classes(img)
    probabilityValue =np.amax(predictions)
    if probabilityValue > threshold:
    #print(getCalssName(classIndex))
        cv2.putText(imgOrignal,str(classIndex)+" "+str(getCalssName(classIndex)), (120, 35), font, 0.75, (0, 0, 255), 2, cv2.LINE_AA)
        cv2.putText(imgOrignal, str(round(probabilityValue*100,2) )+"%", (180, 75), font, 0.75, (0, 0, 255), 2, cv2.LINE_AA)
        cv2.imshow("Result", imgOrignal)
 
    if cv2.waitKey(1) and 0xFF == ord('q'):
        break

Answer 1

You need to install compatible cuda and cudnn versions. Please refer this to know about the build configurations.

OR

If you are working on GPU, the following code suppresses the warning.

# It just disables the warning, doesn't take advantage of AVX to run faster
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'

If you're on Unix,try by setting export TF_CPP_MIN_LOG_LEVEL=3 to disable these warnings. Thanks!