gives the error:
Just alfa-test...
I just use (because its at the top of Main and easy to find)
How much memory does your Python process use? For me it’s uses around 800mb for small images. The large image it requested 12gb but the virtual machine only had 4gb. I realise that’s small but I’m merely pointing out that it can consume a lot of memory. I’m not saying it doesn’t work.
This is a valid question and the answer is no. Java is way behind Python in this field and B4J can only run Java code directly. Just running something on the GPU with Java is a complete mess, and here with Torch you can do it very easily.
public Sub Keras
Dim Code As String=$"
import os
os.environ['TF_CPP_MIN_LOG_LEVEL'] = '3'
os.environ['TF_ENABLE_ONEDNN_OPTS'] = '0'
import tensorflow
import numpy as np
from keras.models import Sequential
from keras.layers import Dense, Input
def kerastest():
print_result = ''
try:
# Input dataset (3 inputs)
inputs = np.array([[1, 0, 0]], dtype=float)
# Output dataset (1 output)
expected_output = np.array([[1]], dtype=float)
# Ensure the input and output data are of the correct shape
if inputs.ndim != 2 or expected_output.ndim != 2:
return "Input and output data must be 2-dimensional"
print_result += f"Input data shape: {inputs.shape}, dtype: {inputs.dtype}"
print_result += f"\nOutput data shape: {expected_output.shape}, dtype: {expected_output.dtype}"
# Create the model
model = Sequential()
# Add the input layer using Input and the first hidden layer
model.add(Input(shape=(3,)))
model.add(Dense(units=3, activation='sigmoid'))
# Add the output layer
model.add(Dense(units=1, activation='sigmoid'))
# Compile the model
model.compile(optimizer='adam', loss='binary_crossentropy', metrics=['accuracy'])
# Train the model
model.fit(inputs, expected_output, epochs=750, verbose=0)
# Make predictions
predicted_output = model.predict(inputs)
print_result += f"\nFinal output after training: {format(predicted_output[0][0],'.0f')}"
return print_result
except Exception as e:
import traceback
error_message = traceback.format_exc() # Capture the traceback as a string
return f"An error occurred:\n{error_message}"
"$
Wait for (Py.Utils.RunCode("kerastest",Null, Code).Fetch) Complete(Result As PyWrapper)
Log(Result.Value.As(String))
End SubSub runFromFile(dir As String,fname As String,method As String,params() As Object) As ResumableSub
Dim Code As String
Code = File.ReadString(dir,fname)
If params=Null Then
Wait for (Py.Utils.RunCode(method, Null, Code).Fetch) Complete(Result As PyWrapper)
Else
Wait for (Py.Utils.RunCode(method, params, Code).Fetch) Complete(Result As PyWrapper)
End If
Return (Result.Value.As(String))
End Sub...
wait for (GPUTest.runFromFile(File.DirAssets,"test.py","major_test",doubleArray(Array("")))) Complete (Result As Object)
Log(Result)
wait for (GPUTest.runFromFile(File.DirAssets,"test.py","major_test",doubleArray(Array("","test")))) Complete (Result As Object)
Log(Result)
wait for (GPUTest.runFromFile(File.DirAssets,"test.py","major_test",doubleArray(Array("","test","2nd Parameter")))) Complete (Result As Object)
Log(Result)
End Sub
private Sub doubleArray(a() As Object) As Object
Return Array(a)
End Subdef test0():
return f"This is from a function in a python script"
def test1(a):
return f"This is from function with a param ({a})"
def test2(a,b):
return f"This is from function with 2 param ({a}, {b})"
def major_test(a):
switch = {
1: lambda: test0(),
2: lambda: test1(a[1]),
3: lambda: test2(a[1],a[2])
}
res = switch.get(len(a),lambda: f"Not Found")()
return resWell as I understand you understood the way working the whole py bridge thing... is it easy to create a thread with comments and a b4xpage with all these ?
Ok can be... recognition counting persons...
What is this?Recognition of 500 objects in the database of the same size, but with small irregular ids on the surface:
Without any way of adding digital ID (like QR- or barcode).
Periodically being added new ones, and removing the existing ones
Industrial vagonets, and my B4J server app that tries to recognize them with help of some Python subsystem via Http API.
