DmitriiSavin
dsavin
commited on
[113] - Handle batches with no gt, Add images with no gt to the dataset (#120)
Browse files
yolo/tools/data_loader.py
CHANGED
@@ -87,9 +87,6 @@ class YoloDataset(Dataset):
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continue
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annotations = annotations_index.get(image_info["id"], [])
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image_seg_annotations = scale_segmentation(annotations, image_info)
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-
if not image_seg_annotations:
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-
continue
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-
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elif data_type == "txt":
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label_path = labels_path / f"{image_id}.txt"
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if not label_path.is_file():
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continue
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annotations = annotations_index.get(image_info["id"], [])
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image_seg_annotations = scale_segmentation(annotations, image_info)
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elif data_type == "txt":
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label_path = labels_path / f"{image_id}.txt"
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if not label_path.is_file():
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yolo/tools/loss_functions.py
CHANGED
@@ -93,7 +93,7 @@ class YOLOLoss:
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targets_cls, targets_bbox = self.separate_anchor(align_targets)
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predicts_box = predicts_box / self.vec2box.scaler[None, :, None]
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-
cls_norm = targets_cls.sum()
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box_norm = targets_cls.sum(-1)[valid_masks]
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## -- CLS -- ##
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targets_cls, targets_bbox = self.separate_anchor(align_targets)
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predicts_box = predicts_box / self.vec2box.scaler[None, :, None]
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+
cls_norm = max(targets_cls.sum(), 1)
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box_norm = targets_cls.sum(-1)[valid_masks]
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## -- CLS -- ##
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