Inference single custom images

[yirs2001]

Hi there, Thanks your code, I want to inference any custom image which is not in Tusimple dataset. The following is my code: import torch import cv2 import torch.nn.functional as F from models.resa import RESANet from utils.config import Config from datasets import build_dataloader from models.registry import build_net

from PIL import Image import utils.transforms as tf from torch.autograd import Variable from torchvision.utils import save_image import torchvision.transforms as transforms

loader1 = transforms.Compose([transforms.ToTensor(), transforms.Normalize((103.939, 116.779, 123.68), (1., 1., 1.)), transforms.Resize((368,640)),]) # for tusimple

def image_loader(image_name): """load image, return cuda tensor""" image = Image.open(image_name) image = loader1(image).float() image = Variable(image, requires_grad=True) image = image.unsqueeze(0) return image.cuda()

cfg = Config.fromfile('configs/tusimple.py')

resa = build_net(cfg) resa = torch.nn.parallel.DataParallel( resa, device_ids = range(1)).cuda()

loader = build_dataloader(cfg.dataset.val, cfg, is_train=False) pretrained_model = torch.load('tusimple_resnet34.pth') resa.load_state_dict(pretrained_model['net'], strict=True)

x = image_loader('./20.jpg') # 20.jpg is copied from tusimple test datasets

with torch.no_grad(): out = resa(x) probmap, exist = out['seg'], out['exist'] probmap = F.softmax(probmap, dim=1).squeeze().cpu().numpy() exist = exist.squeeze().cpu().numpy()

coords = loader.dataset.probmap2lane(probmap, exist)

img = cv2.imread('./20.jpg') loader.dataset.view(img, coords, './test.png')

The result is not as good as choose from x = loader.dataset[img_idx]['img'].unsqueeze(0).cuda() Can you help that? thanks so much.

[Turoad]

what error do you get? By the way,

x = loader.dataset['img_idx]['img'].unsqueeze(0).cuda()

should be

x = loader.dataset[img_idx]['img'].unsqueeze(0).cuda()

[yirs2001]

Sorry, that is a typo. Actually, there is no error during the code execution. I use the same image for my code and the reference code(Inference on custom example #1) The result is different.

thank for your helping

[Turoad]

If you're testing on a image from a different dataset, then there's no guarantee the result is going to be useful. Maybe you can try to train a new model in the new dataset.

[yirs2001]

appreciated your response. For my current experiment, the image is picked from the tusimple dataset. So, I think the result should be the same.

Thanks so much.

[Turoad]

Your pre-process of input image is different from the ours. Please check the __getitem__ in the BaseDataset from https://github.com/ZJULearning/resa/blob/main/datasets/base_dataset.py#L62.

[yirs2001]

Thanks for your response. Yes. the pre-process of input is different. After I modifed the code with that, the result is the same with yours. BTW, I picked couple images which are not in Tusimple or CUlane dataset and the results are perfect.

appreciated!!!

[Turoad]

Congratulations. 😁

[KnightHarute]

I'm struggling with inferencing my custom image. Would you share your inference code, please?

[Turoad]

you can refer to this code: https://github.com/Turoad/lanedet/blob/main/tools/detect.py