simonfranken/mmp_wise2526_franksim
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adapts dataset for test set

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franksim
2025-11-09 12:33:02 +01:00
parent 51b18f1d82
commit 85fd327052
1 changed files with 10 additions and 5 deletions
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15
mmp/a4/dataset.py
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@@ -40,10 +40,13 @@ class MMP_Dataset(torch.utils.data.Dataset):
match = img_pattern.match(fname) match = img_pattern.match(fname)
if match: if match:
img_file = os.path.join(path_to_data, fname) img_file = os.path.join(path_to_data, fname)
annotations = read_groundtruth_file( if is_test:
os.path.join(path_to_data, f"{match.group(1)}.gt_data.txt") self.images.append((img_file, None))
) else:
self.images.append((img_file, annotations)) annotations = read_groundtruth_file(
os.path.join(path_to_data, f"{match.group(1)}.gt_data.txt")
)
self.images.append((img_file, annotations))
self.images.sort( self.images.sort(
key=lambda x: int(re.match(r"(.*/)(\d+)(\.jpg)", x[0]).group(2)) key=lambda x: int(re.match(r"(.*/)(\d+)(\.jpg)", x[0]).group(2))
@@ -66,10 +69,12 @@ class MMP_Dataset(torch.utils.data.Dataset):
] ]
) )
img_tensor = transform(img) img_tensor = transform(img)
img_id = re.match(r".*(\/)([0-9]+)(\.[^\/]*$)", self.images[idx][0]).group(2)
if self.is_test:
return (img_tensor, torch.Tensor(), int(img_id))
label_grid = get_label_grid( label_grid = get_label_grid(
anchor_grid=self.anchor_grid, gts=self.images[idx][1], min_iou=self.min_iou anchor_grid=self.anchor_grid, gts=self.images[idx][1], min_iou=self.min_iou
) )
img_id = re.match(r".*(\/)([0-9]+)(\.[^\/]*$)", self.images[idx][0]).group(2)
return (img_tensor, label_grid, int(img_id)) return (img_tensor, label_grid, int(img_id))
def __len__(self) -> int: def __len__(self) -> int: