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changed yolo dataset for no label images

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marvin
2026-06-05 14:31:40 +02:00
parent fe90bfa39b
commit 760caefbfe
2 changed files with 0 additions and 4 deletions
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api/src/yolo/train_yolo_faces.py
-1
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@@ -34,7 +34,6 @@ def visualize_boxes(label, image, threshold=0.95):
boxes_to_draw, grids_to_draw_obj, grids_to_draw_noobj = convert_prediction(label, image, threshold) boxes_to_draw, grids_to_draw_obj, grids_to_draw_noobj = convert_prediction(label, image, threshold)
if len(boxes_to_draw) == 0: if len(boxes_to_draw) == 0:
print("no labels") print("no labels")
return
boxes_to_draw = torch.tensor(boxes_to_draw) boxes_to_draw = torch.tensor(boxes_to_draw)
grids_to_draw_noobj = torch.tensor(grids_to_draw_noobj) grids_to_draw_noobj = torch.tensor(grids_to_draw_noobj)
grids_to_draw_obj = torch.tensor(grids_to_draw_obj) grids_to_draw_obj = torch.tensor(grids_to_draw_obj)
api/src/yolo/yolo_dataset.py
-3
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@@ -119,9 +119,6 @@ class YoloDataset(Dataset):
boxes = augmented["bboxes"] boxes = augmented["bboxes"]
labels = augmented["labels"] labels = augmented["labels"]
if len(boxes) == 0:
return self.__getitem__((idx + 1) % len(self.image_ids))
ground_truth = list(zip(boxes, labels)) ground_truth = list(zip(boxes, labels))
#[S, S, (x+y+w+h+c+C)] #[S, S, (x+y+w+h+c+C)]
targets = np.zeros((self.grid, self.grid, 5 + self.num_classes), dtype=np.float32) targets = np.zeros((self.grid, self.grid, 5 + self.num_classes), dtype=np.float32)