Yolov8 Roboflow Notebook Error - Albumentations Package #311
Description
Search before asking
- I have searched the Roboflow Notebooks issues and found no similar bug report.
Notebook name
Notebook: YOLOv8 Object Detection
Bug
When beginning training on the first epoch, this unhashable type error arises:
Traceback (most recent call last): File "/usr/local/bin/yolo", line 8, in <module> sys.exit(entrypoint()) File "/usr/local/lib/python3.10/dist-packages/ultralytics/cfg/__init__.py", line 445, in entrypoint getattr(model, mode)(**overrides) # default args from model File "/usr/local/lib/python3.10/dist-packages/ultralytics/engine/model.py", line 341, in train self.trainer.train() File "/usr/local/lib/python3.10/dist-packages/ultralytics/engine/trainer.py", line 191, in train self._do_train(world_size) File "/usr/local/lib/python3.10/dist-packages/ultralytics/engine/trainer.py", line 325, in _do_train for i, batch in pbar: File "/usr/local/lib/python3.10/dist-packages/tqdm/std.py", line 1181, in __iter__ for obj in iterable: File "/usr/local/lib/python3.10/dist-packages/ultralytics/data/build.py", line 42, in __iter__ yield next(self.iterator) File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py", line 630, in __next__ data = self._next_data() File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py", line 1344, in _next_data return self._process_data(data) File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py", line 1370, in _process_data data.reraise() File "/usr/local/lib/python3.10/dist-packages/torch/_utils.py", line 706, in reraise raise exception TypeError: Caught TypeError in DataLoader worker process 0. Original Traceback (most recent call last): File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/worker.py", line 309, in _worker_loop data = fetcher.fetch(index) # type: ignore[possibly-undefined] File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py", line 52, in fetch data = [self.dataset[idx] for idx in possibly_batched_index] File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py", line 52, in <listcomp> data = [self.dataset[idx] for idx in possibly_batched_index] File "/usr/local/lib/python3.10/dist-packages/ultralytics/data/base.py", line 242, in __getitem__ return self.transforms(self.get_image_and_label(index)) File "/usr/local/lib/python3.10/dist-packages/ultralytics/data/augment.py", line 70, in __call__ data = t(data) File "/usr/local/lib/python3.10/dist-packages/ultralytics/data/augment.py", line 824, in __call__ new = self.transform(image=im, bboxes=bboxes, class_labels=cls) # transformed File "/usr/local/lib/python3.10/dist-packages/albumentations/core/composition.py", line 334, in __call__ self.preprocess(data) File "/usr/local/lib/python3.10/dist-packages/albumentations/core/composition.py", line 368, in preprocess p.preprocess(data) File "/usr/local/lib/python3.10/dist-packages/albumentations/core/utils.py", line 125, in preprocess data = self.add_label_fields_to_data(data) File "/usr/local/lib/python3.10/dist-packages/albumentations/core/utils.py", line 185, in add_label_fields_to_data encoded_labels = encoder.fit_transform(data[label_field]) File "/usr/local/lib/python3.10/dist-packages/albumentations/core/utils.py", line 60, in fit_transform self.fit(y) File "/usr/local/lib/python3.10/dist-packages/albumentations/core/utils.py", line 48, in fit unique_labels = sorted(set(y)) TypeError: unhashable type: 'numpy.ndarray'
Environment
- Google Colab
- Ultralytics YOLOv8.0.196 🚀 Python-3.10.12 torch-2.4.1+cu121 CUDA:0 (Tesla T4, 15102MiB)
Setup complete ✅ (2 CPUs, 12.7 GB RAM, 32.6/112.6 GB disk)
Minimal Reproducible Example
%cd {HOME}
!yolo task=detect mode=train model=yolov8s.pt data={dataset.location}/data.yaml epochs=300 imgsz=640 plots=True
Additional
Ran the notebook tutorial, importing my own dataset from roboflow (tried several datasets), under "Custom Training" this error occurs each time.
Last successful training used torch 2.4.0, currently torch 2.4.1 is being loaded.
Are you willing to submit a PR?
- Yes I'd like to help by submitting a PR!