resnet50

Halcom

1. # -*- coding: utf-8 -*-
   
2. """
   
3. Created on Wed Sep 17 11:03:53 2025
   
4. @author: WITIAI
   
5. """
   
6. import argparse
   
7. import numpy as np
   
8. import numpy as np
   
9. import torch
   
10. import torchvision.models.resnet as resnet
    
11. import torchvision.transforms as transforms
    
12. import torch.nn as nn
    
13. import torchvision.models.resnet as resnet
    
14. import struct
    
15. import os
    
16. import sys
    
17. import cv2
    
18. 
    
19. resnet50 = resnet.resnet50(pretrained=False)
    
20. modelpath=r'D:\0_WITIAI\Software_Package\Python3109\python3109amd64\Lib\site-packages\models_witiai\resnet50_class.pth'
    
21. resnet50.load_state_dict(torch.load(modelpath))
    
22. resnet50.eval()
    
23. dic = resnet50.state_dict()
    
24. 
    
25. imagepath = r'C:\WitiaiCvCodes\testimages\teddy.bmp'
    
26. img = cv2.imread(imagepath)  # reading that image as array
    
27. if(img.shape[2] == 3):
    
28.     img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)
    
29. elif(img.shape[2] == 1):
    
30.     img = cv2.cvtColor(img, cv2.COLOR_GRAY2RGB)
    
31. im_size = 224
    
32. img = cv2.resize(img, (im_size, im_size)) # color image
    
33. x_transforms = transforms.Compose([transforms.ToTensor(), transforms.Normalize([0.5, 0.5, 0.5], [0.5, 0.5, 0.5]) ])
    
34. image = x_transforms(img)
    
35. print(image.size())
    
36. image = image.unsqueeze(0)
    
37. print(image.size())

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