Writing Python script for the NCS-2

[Bbill14]

Hello everyone

I'm a new user of the NCS-2 and need a help on the creation of a testing script to use it with NCS-2 on Raspberry Pi. To start by creating a CNN to classify a Digit from 0 to 9, using the example described in the link below.

https://www.youtube.com/watch?v=y1ZrOs9s2QA

I have saved a Keras model, next, I turn Keras to TensorFlow model. By using the model optimizer I have converted the Tensorflow model to an IR file (.bin and .xml files) that we can use on the Neural Compute Stick 2.

I have run the following Python script on CPU and he is working as expected,  

###################################################

import numpy as np

import cv2

from keras.models import load_model

########### PARAMETERS ##############

threshold = 0.65 # MINIMUM PROBABILITY TO CLASSIFY

#####################################

#%%

#### LOAD THE TRAINNED MODEL 

model = load_model('./keras_model/model_keras.h5')

#%%

#### PREPORCESSING FUNCTION

def preProcessing(img):

  img = cv2.cvtColor(img,cv2.COLOR_BGR2GRAY)

  img = cv2.equalizeHist(img)

  img = img/255

  return img

#%%

imgOriginal = cv2.imread('cap5.png')

img = np.asarray(imgOriginal)

img = cv2.resize(img,(32,32))

img = preProcessing(img)

cv2.imshow("Processed Image", img)

img = img.reshape(1,32,32,1)

#### PREDICT

classIndex = int(model.predict_classes(img))

print(classIndex)

predictions = model.predict(img)

print(predictions)

probVal= np.amax(predictions)

print(classIndex,probVal)

if probVal> threshold:

  cv2.putText(imgOriginal,str(classIndex) + "  "+str(probVal),

        (50,50),cv2.FONT_HERSHEY_COMPLEX,

        1,(0,0,255),1)

  cv2.imwrite('cap5_pre.png',imgOriginal)

###################################################

Now I need help with writing the testing script for the NCS-2 using the Openvino inference engine functions (IENetwork, IEPlugin).

Can anyone help me to do it?

Thanks

[David_C_Intel]

Hi Bengherbia,

Thanks for reaching out. It seems you already started a similar thread here.

If possible, let's keep the comments on that thread only.

Best regards,

David 

[SSola8]

Just to keep it organized for developers like us, I have posted my answer there.