removed more non verbos guarded prints
@@ -150,7 +150,6 @@ class VideoSubSequence(Dataset):
label_name = self._get_label_name(unique_label)
class_label = self.classmap[label_name]
# Convert instance label to object class label
- print("converting", unique_label, "to", class_label)
target[target == unique_label] = class_label
return target
@@ -492,7 +491,6 @@ class EndlessCLSimDataset(DownloadableDataset):
def _load_metadata(self) -> bool:
# If a 'named'-scenario has been selected
if self.scenario is not None:
- print("using named scenario")
# Get data name
scenario_data_name = self._get_scenario_data()
scenario_data_name = scenario_data_name[0].split(".")[0]
@@ -509,7 +507,6 @@ class EndlessCLSimDataset(DownloadableDataset):
"Two directories match the selected scenario!")
match_path = str(self.root / name)
- print("match_path:", match_path)
if match_path is None:
return False
@@ -518,7 +515,6 @@ class EndlessCLSimDataset(DownloadableDataset):
self._prepare_classification_subsequence_datasets(
match_path)
else:
- print("preparing video..")
is_subsequence_preparation_done = \
self._prepare_video_subsequence_datasets(match_path)
@@ -534,7 +530,6 @@ class EndlessCLSimDataset(DownloadableDataset):
self._prepare_classification_subsequence_datasets(
str(self.root))
else:
- print("preparing video..")
is_subsequence_preparation_done = \
self._prepare_video_subsequence_datasets(
str(self.root))
@@ -575,7 +570,10 @@ if __name__ == "__main__":
_default_transform = transforms.Compose([
transforms.ToTensor()])
- data = EndlessCLSimDataset(scenario="Classes", root="/data/avalanche",
+ # data = EndlessCLSimDataset(scenario="Classes", root="/data/avalanche",
+ # semseg=True, transform=_default_transform)
+ data = EndlessCLSimDataset(scenario=None, download=False,
+ root="/data/avalanche/IncrementalClasses_Video",
semseg=True, transform=_default_transform)
print("num subseqeunces:", len(data.train_sub_sequence_datasets))
