erik Hello Erik, I hope you are doing great. Thanks for your help. I managed to get around the problem i was facing, to solve it for now I removed the normalization code from the model training and retrained my model. So now I do not need to add a neural network node for normalization.
I have one other problem which I also asked you earlier in this thread. I have three patches extracted from same camera frame using three ImageManip nodes and I need to pass them through same neural network one by one. You suggested to use script node can you please explain a little more how can I do that. How can i use script in between to network nodes.
I have pasted my code below for your reference. At the moment i am just passing one image patch through the network. I have uncommented the other two ImageManip nodes in code so that you can see what I want to do. Right I am just passing output manip_time node through network. You might think I am missing connections of two ImageManip nodes but i just added them for you to understand what i want.
import depthai as dai
import numpy as np
manip_time = pipeline.create(dai.node.ImageManip)
nn = pipeline.create(dai.node.NeuralNetwork)
pipeline = dai.Pipeline()
model_path = 'crnn_99_soft_no_norm.blob'
cam = pipeline.create(dai.node.MonoCamera)
nn_Out = pipeline.create(dai.node.XLinkOut)
with dai.Device(pipeline) as device:
nn_queue = device.getOutputQueue(name="rec_time", maxSize=4, blocking=False)
nn_out = nn_queue.get()
if nn_out is not None:
for i in range(24):
for l in raw_preds:
if l != previous:
previous = l
results = [l for l in results if l != 0]