Hello guys!
I'm using Delphi 10.4.2 and Python4Delphi with Python 3.9.2 Win64
I have the error "Access Violation at address in module python39.dll"
the error continues even in the property of PythonEngine.DllName = python39.dll
and
PythonEngine.DllName = C:\Users\Administrator\AppData\Local\Programs\Python\Python39
a curiosity is that my code is running in VS Studio.
can anybody help me ? Thanks
my code:
unit Unit1;
interface
uses
Classes, SysUtils,
Windows, Messages, Graphics, Controls, Forms, Dialogs,
StdCtrls, ComCtrls, ExtCtrls,
PythonEngine, Vcl.PythonGUIInputOutput, SynEditHighlighter,
SynEditCodeFolding, SynHighlighterPython, SynEditPythonBehaviour, SynEdit;
type
TForm1 = class(TForm)
Memo1: TMemo;
Panel1: TPanel;
Button1: TButton;
Splitter1: TSplitter;
Button2: TButton;
Button3: TButton;
OpenDialog1: TOpenDialog;
SaveDialog1: TSaveDialog;
PythonGUIInputOutput1: TPythonGUIInputOutput;
SynEdit1: TSynEdit;
SynEditPythonBehaviour1: TSynEditPythonBehaviour;
SynPythonSyn1: TSynPythonSyn;
PythonEngine1: TPythonEngine;
procedure Button1Click(Sender: TObject);
procedure Button2Click(Sender: TObject);
procedure Button3Click(Sender: TObject);
private
{ Déclarations privées }
public
{ Déclarations publiques }
end;
var
Form1: TForm1;
implementation
{$R *.DFM}
procedure TForm1.Button1Click(Sender: TObject);
begin
GetPythonEngine.ExecString(UTF8Encode(SynEdit1.Text));
end;
procedure TForm1.Button2Click(Sender: TObject);
begin
with OpenDialog1 do
begin
if Execute then
Memo1.Lines.LoadFromFile(FileName);
end;
end;
code python:
import sysconfig
import sys
from cv2 import cv2
import pathlib
import os
import numpy as np
import matplotlib.pyplot as plt
from PIL import Image, ImageDraw
import random
import shutil
import zipfile
from tqdm import tqdm
import torch
import torchvision
from torch.utils.data import DataLoader, Dataset
from torchvision.datasets import ImageFolder
from torchvision import transforms
import random
from time import time
from torch.utils.data import random_split
caminho_do_modelo_no_google_drive = r'C:\Users\300.pt'
model = torch.load(caminho_do_modelo_no_google_drive, map_location='cpu')
lista_violento = list(pathlib.Path(r'C:\cam2').glob('*'))
lista_nao_violento = list(pathlib.Path(r'C:\cam1').glob('*'))
print ('Quantidade de Vídeos Violentos:',len(lista_violento))
print ('Quantidade de Vídeos Não Violentos:',len(lista_nao_violento))
transformer = transforms.Compose([
transforms.Resize(150),
transforms.ToTensor(),
transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225])
])
vetor_classes = ['non-violent', 'violent']
def retirar_frame_a_frame_e_fazer_predicoes_e_plotar(path_video, y_true):
violent_count = 0
non_violent_count = 0
contador = 0
vetor_probs = []
vetor_labels = []
vetor_imagens = []
cap = cv2.VideoCapture(path_video)
while (cap.isOpened()):
ret, frame = cap.read()
if (ret == False):
break
img = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
img_pil = Image.fromarray(img)
vetor_imagens.append(img_pil)
img_tensor = transformer(img_pil)
img_tensor.unsqueeze_(0)
resultado = model.forward(img_tensor)
probs = torch.exp(resultado)
probs = probs.max(1)
probabilidade = probs[0].detach().numpy()[0]
vetor_probs.append(probabilidade)
label_predita = probs[1].detach().numpy()[0]
vetor_labels.append(label_predita)
contador += 1
if (label_predita == 1):
violent_count += 1
else:
non_violent_count += 1
taxa_frames_violentos = 100*violent_count/contador
taxa_frames_nao_violentos = 100*non_violent_count/contador
plt.figure(figsize=(15, 10))
for k in range(9):
plt.subplot(3, 3, k+1)
n = random.randint(0, len(vetor_probs)-1)
img = vetor_imagens[n]
label = vetor_labels[n]
plt.imshow(img)
plt.xticks([])
plt.yticks([])
plt.title('Real: {0}\nPredito: {1}'.format(vetor_classes[y_true], vetor_classes[label]))
plt.show()
return np.array(vetor_probs), np.array(vetor_labels), taxa_frames_violentos, taxa_frames_nao_violentos
model.to('cpu')
model.eval()
video = str(random.choice(lista_nao_violento))
print ('Para o vídeo: ' + video)
vetor_probs, vetor_labels, taxa_frames_violentos, taxa_frames_nao_violentos = retirar_frame_a_frame_e_fazer_predicoes_e_plotar(video, 1)
print ('taxa frames 1: {0:.2f}'.format(taxa_frames_nao_violentos))
print ('taxa frames 2: {0:.2f}'.format(taxa_frames_violentos))
#, sys.path sys.executable
#print(sys.version)
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