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1 year ago 👋 Hello @pippo97-jpg, thank you for leaving an issue on Roboflow Notebooks.
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SkalskiP
pippo97-jpg
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Notebook name
How-to-train-yolov8-instance-segmentation-on-custom-dataset.ipynb
Bug
Traceback (most recent call last): File "/usr/local/bin/yolo", line 8, in
sys.exit(entrypoint())
File "/usr/local/lib/python3.9/dist-packages/ultralytics/yolo/cfg/init.py", line 266, in entrypoint
getattr(model, mode)(**vars(cfg))
File "/usr/local/lib/python3.9/dist-packages/ultralytics/yolo/engine/model.py", line 214, in train
self.trainer.train()
File "/usr/local/lib/python3.9/dist-packages/ultralytics/yolo/engine/trainer.py", line 182, in train
self._do_train(int(os.getenv("RANK", -1)), world_size)
File "/usr/local/lib/python3.9/dist-packages/ultralytics/yolo/engine/trainer.py", line 301, in _do_train
self.loss, self.loss_items = self.criterion(preds, batch)
File "/usr/local/lib/python3.9/dist-packages/ultralytics/yolo/v8/segment/train.py", line 44, in criterion
return self.compute_loss(preds, batch)
File "/usr/local/lib/python3.9/dist-packages/ultralytics/yolo/v8/segment/train.py", line 85, in call
targets = torch.cat((batch_idx, batch["cls"].view(-1, 1), batch["bboxes"]), 1)
RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 49 but got size 0 for tensor number 1 in the list.
Sentry is attempting to send 1 pending error messages
Waiting up to 2 seconds
Environment
-Google colab -Python 3.9
Minimal Reproducible Example
%cd {HOME}
!yolo task=segment mode=train model=yolov8m-seg.pt data={dataset.location}/data.yaml epochs=25 imgsz=640
Additional
/content Downloading https://github.com/ultralytics/assets/releases/download/v0.0.0/yolov8m-seg.pt to yolov8m-seg.pt... 100% 52.4M/52.4M [00:05<00:00, 10.6MB/s] Ultralytics YOLOv8.0.28 🚀 Python-3.9.16 torch-2.0.0+cu118 CUDA:0 (Tesla T4, 15102MiB) yolo/engine/trainer: task=segment, mode=train, model=yolov8m-seg.pt, data=/content/datasets/Planeat-food-Instance-Segmentation-7/data.yaml, epochs=25, patience=50, batch=16, imgsz=640, save=True, cache=False, device=None, workers=8, project=None, name=None, exist_ok=False, pretrained=False, optimizer=SGD, verbose=True, seed=0, deterministic=True, single_cls=False, image_weights=False, rect=False, cos_lr=False, close_mosaic=10, resume=False, overlap_mask=True, mask_ratio=4, dropout=0.0, val=True, save_json=False, save_hybrid=False, conf=None, iou=0.7, max_det=300, half=False, dnn=False, plots=True, source=None, show=False, save_txt=False, save_conf=False, save_crop=False, hide_labels=False, hide_conf=False, vid_stride=1, line_thickness=3, visualize=False, augment=False, agnostic_nms=False, classes=None, retina_masks=False, boxes=True, format=torchscript, keras=False, optimize=False, int8=False, dynamic=False, simplify=False, opset=None, workspace=4, nms=False, lr0=0.01, lrf=0.01, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=7.5, cls=0.5, dfl=1.5, fl_gamma=0.0, label_smoothing=0.0, nbs=64, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=0.0, translate=0.1, scale=0.5, shear=0.0, perspective=0.0, flipud=0.0, fliplr=0.5, mosaic=1.0, mixup=0.0, copy_paste=0.0, cfg=None, v5loader=False, save_dir=runs/segment/train Downloading https://ultralytics.com/assets/Arial.ttf to /root/.config/Ultralytics/Arial.ttf... 100% 755k/755k [00:00<00:00, 843kB/s] 2023-04-27 15:34:30.199497: I tensorflow/core/platform/cpu_feature_guard.cc:182] This TensorFlow binary is optimized to use available CPU instructions in performance-critical operations. To enable the following instructions: AVX2 AVX512F FMA, in other operations, rebuild TensorFlow with the appropriate compiler flags. 2023-04-27 15:34:31.234140: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT Overriding model.yaml nc=80 with nc=121
Are you willing to submit a PR?