check if i can leave image name in target as return from dataset ... to(DEVICE) problematic

This commit is contained in:
Till Raab 2023-10-26 09:25:02 +02:00
parent 72c58af7e4
commit 0adfc22ec4
2 changed files with 4 additions and 14 deletions

View File

@ -50,26 +50,13 @@ class CustomDataset(Dataset):
target["iscrowd"] = iscrowd
image_id = torch.tensor([idx])
target["image_id"] = image_id
# target["image_name"] = image_name #ToDo: implement this as 3rd return...
target["image_name"] = image_name #ToDo: implement this as 3rd return...
return img_tensor, target
def __len__(self):
return len(self.all_images)
def create_train_test_dataset(path, test_size=0.2):
files = glob.glob(os.path.join(path, '*.png'))
train_test_idx = np.arange(len(files), dtype=int)
np.random.shuffle(train_test_idx)
train_idx = train_test_idx[int(test_size*len(train_test_idx)):]
test_idx = train_test_idx[:int(test_size*len(train_test_idx))]
train_data = CustomDataset(path)
test_data = CustomDataset(path)
return train_data, test_data
def create_train_or_test_dataset(path, train=True):
if train == True:
pfx='train'

View File

@ -45,6 +45,9 @@ def infere_model(test_loader, model, detection_th=0.8):
prog_bar = tqdm(test_loader, total=len(test_loader))
for samples, targets in prog_bar:
images = list(image.to(DEVICE) for image in samples)
embed()
quit()
targets = [{k: v for k, v in t.items()} for t in targets]
with torch.inference_mode():