ValueError: not enough values to unpack (expected 3, got 0) YOLOv5_obb #12942
Comments
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👋 Hello @yasmine-lkl, thank you for your interest in YOLOv5 🚀! Please visit our ⭐️ Tutorials to get started, where you can find quickstart guides for simple tasks like Custom Data Training all the way to advanced concepts like Hyperparameter Evolution. If this is a 🐛 Bug Report, please provide a minimum reproducible example to help us debug it. If this is a custom training ❓ Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results. RequirementsPython>=3.8.0 with all requirements.txt installed including PyTorch>=1.8. To get started: git clone https://github.com/ultralytics/yolov5 # clone
cd yolov5
pip install -r requirements.txt # installEnvironmentsYOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
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If this badge is green, all YOLOv5 GitHub Actions Continuous Integration (CI) tests are currently passing. CI tests verify correct operation of YOLOv5 training, validation, inference, export and benchmarks on macOS, Windows, and Ubuntu every 24 hours and on every commit. Introducing YOLOv8 🚀We're excited to announce the launch of our latest state-of-the-art (SOTA) object detection model for 2023 - YOLOv8 🚀! Designed to be fast, accurate, and easy to use, YOLOv8 is an ideal choice for a wide range of object detection, image segmentation and image classification tasks. With YOLOv8, you'll be able to quickly and accurately detect objects in real-time, streamline your workflows, and achieve new levels of accuracy in your projects. Check out our YOLOv8 Docs for details and get started with: pip install ultralytics |
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Hello! It looks like you're encountering an issue where your dataset might not be properly formatted or recognized by the YOLOv5 OBB (oriented bounding boxes) training process. This specific error typically arises when the training script fails to load any annotations from your dataset, possibly due to incompatible or corrupt files. Here's a quick checklist to help resolve the issue:
Given the error message: This implies the If after these steps you're still facing issues, consider revisiting the dataset preparation stage, ensuring that your data is exported in a compatible format for YOLOv5 OBB training. Also, consult the documentation available at the official GitHub repository and repositories providing OBB support for additional guidance on data preparation and troubleshooting. I hope this helps! If you have more details or other errors come up, feel free to share them for more specific advice. 🙂 |
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It seems like the issue might still be related to how the annotations or the dataset are handled in your setup. Commenting out Given that you've checked the format and paths without resolution, it might be insightful to ensure the environment setup, particularly around the NMS (Non-Maximum Suppression) for rotated bounding boxes, is correctly configured as per the requirements for YOLOv5 OBB. If the script was throwing errors related to Since direct modification of the codebase can introduce hard-to-track issues, I recommend:
If after addressing these points the problem persists, sharing the specific error message related to Hope this helps guide you towards a resolution! 🚀 |
Thank you very much for your detailed response! Indeed, I tried uncommenting the line "from . import nms_rotated_ext" as suggested, but it led to the exact error : /content/yolov5_obb |
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Thanks for sharing the specific error message! It looks like there might be a circular import or a problem with compiling the
If these suggestions don't resolve the issue, you might consider isolating the test code to a simpler environment or dig deeper into the Hope this helps you move forward! 👍 |
Thank you for providing such detailed suggestions! I attempted to install PyTorch with the specified version (1.12.1+cu113) as recommended in the YOLOv5 OBB documentation. Unfortunately, I encountered difficulties during installation on Colab. Despite my efforts to use the following command: !pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 -f https://download.pytorch.org/whl/cu11 Colab refused to accept this installation and upgraded PyTorch to version 12.2. I suspect there might be an incompatibility between CUDA and PyTorch. Could you advise me on the best version of PyTorch to use with CUDA and how to resolve this issue in the Colab environment? Would the validated versions (10.0/10.1/10.2/11.3) be a better option? Additionally, when installing the requirements, I encountered this error: "RuntimeError: The detected CUDA version (12.2) mismatches the version that was used to compile". Any additional assistance would be greatly appreciated. Thank you again for your help! |
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Hello! It seems like you're facing a known issue with package installations on Google Colab, since it often comes with pre-installed packages that can interfere with specific version requests. To ensure you can install the exact PyTorch version you need, you can use the !pip install torch==1.12.1+cu113 torchvision==0.13.1+cu113 torchaudio==0.12.1 -f https://download.pytorch.org/whl/cu113 --force-reinstallThis command should help overwrite any existing installations with the specified versions. Regarding PyTorch and CUDA compatibility, it's vital to match the versions accurately to the ones specified in the setup or as close as possible. For Colab, using CUDA 11.3 with the corresponding PyTorch build that supports this version is usually reliable. If you continue to encounter mismatches or errors, you might need to reset your runtime (via 'Runtime' > 'Restart runtime...' in Colab) to clear any pre-existing installations before running the install command again. Let me know if this resolves the issue or if further adjustments are needed! 🚀 |
Thank you very much for your detailed response and suggestions! I followed your advice and attempted to execute the command with the --force-reinstall flag to install the specified versions of PyTorch. However, I encountered an error stating that no matching version for torch==1.12.1+cu113 was found : "Looking in links: https://download.pytorch.org/whl/cu113 Subsequently, I re-ran the command :"!pip install torch==1.12.1 torchvision==0.13.1 torchaudio==0.12.1 -f https://download.pytorch.org/whl/cu113 --force-reinstallwith the torch==1.12.1 version". This resulted in a successful installation, when I checked the CUDA version using Additionally, while checking the torch version using Do you have any further suggestions for resolving this issue? I am open to any additional recommendations to align PyTorch, CUDA versions, and resolve this circular import error. Your assistance is greatly appreciated! Thank you again for your ongoing support. |
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Hello! It seems like the correct version of PyTorch compatible with CUDA 11.3 might not be available through the link you used. Let's try to directly request the package that aligns with CUDA 11.3 to resolve this issue: Instead of specifying !pip install torch torchvision torchaudio --force-reinstallAfter running this, verify the installation by checking the PyTorch and CUDA versions again: import torch
print("Torch version:", torch.__version__)
print("CUDA version installed by PyTorch:", torch.version.cuda)This should ideally align the installed versions to the Colab's CUDA. If the issue with Furthermore, if Let me know how it goes, and if there's anything else I can do to help! 🚀 |
Hello, I'm currently attempting to train my data on Google Colab using YOLOv5 with oriented bounding boxes (YOLOv5 OBB). I annotated my images on CVAT with corrected orientations. However, when using only YOLOv5, the bounding boxes are horizontal, whereas I require them to be in the correct orientation. To address this, I uploaded my images and their annotations to Roboflow and exported them using YOLOv5 Oriented Bounding Boxes. I followed the tutorial provided at https://blog.roboflow.com/yolov5-for-oriented-object-detection/, but I encountered the following error. (All the data I'm using has been uploaded to Roboflow, as mentioned earlier, so my annotations should be in the correct format).
/content/yolov5_obb
2024-04-18 13:52:34.956689: E external/local_xla/xla/stream_executor/cuda/cuda_dnn.cc:9261] Unable to register cuDNN factory: Attempting to register factory for plugin cuDNN when one has already been registered
2024-04-18 13:52:34.956736: E external/local_xla/xla/stream_executor/cuda/cuda_fft.cc:607] Unable to register cuFFT factory: Attempting to register factory for plugin cuFFT when one has already been registered
2024-04-18 13:52:34.958590: E external/local_xla/xla/stream_executor/cuda/cuda_blas.cc:1515] Unable to register cuBLAS factory: Attempting to register factory for plugin cuBLAS when one has already been registered
2024-04-18 13:52:36.030586: W tensorflow/compiler/tf2tensorrt/utils/py_utils.cc:38] TF-TRT Warning: Could not find TensorRT
train: weights=weights/yolov5n.pt, cfg=, data=/content/datasets/roboflow/data.yaml, hyp=data/hyps/obb/hyp.finetune_dota.yaml, epochs=10, batch_size=1, imgsz=1024, rect=False, resume=False, nosave=False, noval=False, noautoanchor=False, evolve=None, bucket=, cache=None, image_weights=False, device=0, multi_scale=False, single_cls=False, adam=False, sync_bn=False, workers=8, project=runs/train, name=exp, exist_ok=True, quad=False, linear_lr=False, label_smoothing=0.0, patience=100, freeze=[0], save_period=-1, local_rank=-1, entity=None, upload_dataset=False, bbox_interval=-1, artifact_alias=latest
github: up to date with https://github.com/hukaixuan19970627/yolov5_obb ✅
YOLOv5 🚀 b00c3f2 torch 2.2.1+cu121 CUDA:0 (NVIDIA A100-SXM4-40GB, 40514MiB)
hyperparameters: lr0=0.01, lrf=0.2, momentum=0.937, weight_decay=0.0005, warmup_epochs=3.0, warmup_momentum=0.8, warmup_bias_lr=0.1, box=0.05, cls=0.5, cls_pw=1.0, theta=0.5, theta_pw=1.0, obj=1.0, obj_pw=1.0, iou_t=0.2, anchor_t=4.0, fl_gamma=0.0, hsv_h=0.015, hsv_s=0.7, hsv_v=0.4, degrees=180.0, translate=0.1, scale=0.25, shear=0.0, perspective=0.0, flipud=0.5, fliplr=0.5, mosaic=0.75, mixup=0.1, copy_paste=0.0, cls_theta=180, csl_radius=2.0
Weights & Biases: run 'pip install wandb' to automatically track and visualize YOLOv5 🚀 runs (RECOMMENDED)
TensorBoard: Start with 'tensorboard --logdir runs/train', view at http://localhost:6006/
Downloading https://github.com/ultralytics/yolov5/releases/download/v7.0/yolov5n.pt to weights/yolov5n.pt...
100% 3.87M/3.87M [00:00<00:00, 151MB/s]
Overriding model.yaml nc=80 with nc=4
0 -1 1 1760 models.common.Conv [3, 16, 6, 2, 2]
1 -1 1 4672 models.common.Conv [16, 32, 3, 2]
2 -1 1 4800 models.common.C3 [32, 32, 1]
3 -1 1 18560 models.common.Conv [32, 64, 3, 2]
4 -1 2 29184 models.common.C3 [64, 64, 2]
5 -1 1 73984 models.common.Conv [64, 128, 3, 2]
6 -1 3 156928 models.common.C3 [128, 128, 3]
7 -1 1 295424 models.common.Conv [128, 256, 3, 2]
8 -1 1 296448 models.common.C3 [256, 256, 1]
9 -1 1 164608 models.common.SPPF [256, 256, 5]
10 -1 1 33024 models.common.Conv [256, 128, 1, 1]
11 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
12 [-1, 6] 1 0 models.common.Concat [1]
13 -1 1 90880 models.common.C3 [256, 128, 1, False]
14 -1 1 8320 models.common.Conv [128, 64, 1, 1]
15 -1 1 0 torch.nn.modules.upsampling.Upsample [None, 2, 'nearest']
16 [-1, 4] 1 0 models.common.Concat [1]
17 -1 1 22912 models.common.C3 [128, 64, 1, False]
18 -1 1 36992 models.common.Conv [64, 64, 3, 2]
19 [-1, 14] 1 0 models.common.Concat [1]
20 -1 1 74496 models.common.C3 [128, 128, 1, False]
21 -1 1 147712 models.common.Conv [128, 128, 3, 2]
22 [-1, 10] 1 0 models.common.Concat [1]
23 -1 1 296448 models.common.C3 [256, 256, 1, False]
24 [17, 20, 23] 1 255717 models.yolo.Detect [4, [[10, 13, 16, 30, 33, 23], [30, 61, 62, 45, 59, 119], [116, 90, 156, 198, 373, 326]], [64, 128, 256]]
Model Summary: 270 layers, 2012869 parameters, 2012869 gradients, 5.0 GFLOPs
Transferred 343/349 items from weights/yolov5n.pt
Scaled weight_decay = 0.0005
optimizer: SGD with parameter groups 57 weight, 60 weight (no decay), 60 bias
albumentations: Blur(always_apply=False, p=0.01, blur_limit=(3, 7)), MedianBlur(always_apply=False, p=0.01, blur_limit=(3, 7)), ToGray(always_apply=False, p=0.01), CLAHE(always_apply=False, p=0.01, clip_limit=(1, 4.0), tile_grid_size=(8, 8))
/usr/lib/python3.10/multiprocessing/popen_fork.py:66: RuntimeWarning: os.fork() was called. os.fork() is incompatible with multithreaded code, and JAX is multithreaded, so this will likely lead to a deadlock.
self.pid = os.fork()
train: Scanning '../datasets/roboflow/train/labelTxt' images and labels...66 found, 0 missing, 0 empty, 66 corrupted: 100% 66/66 [00:00<00:00, 3156.85it/s]
train: WARNING: ../datasets/roboflow/train/images/101_0080_0032_JPG.rf.acaf4287508e8d1650330bb3493a5cd0.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0075_JPG.rf.c3225df3710f0cdb6781510677712ab6.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0077_JPG.rf.edeff5715e98386e970cb851785732d0.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0079_JPG.rf.3f5e3abcba00c3137f09d9a8157a9ce3.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0080_JPG.rf.2ea1352d02087a8940d010a00a7b63bc.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0085_JPG.rf.c9759d24aac28ee3b8674b63e3c31330.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0091_JPG.rf.01e5324a8466aebebc78f8e68fb81d4e.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0093_JPG.rf.f2869c04875e6ac37b09c40f6e7ce991.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0096_JPG.rf.a0ddf088c6f46c55c197aa9aa78af018.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0097_JPG.rf.722bccf6874b4af1ccc3ed94e7493a30.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0100_JPG.rf.794fd877c85e962596ab497704c0d111.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0080_0101_JPG.rf.6fb84dd979858d52cdfcd17427388662.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0004_JPG.rf.d862fa1ce430fecf1d9debcbeb545fe4.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0009_JPG.rf.dfd9912d103379ed981fed3e06ad3a51.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0023_JPG.rf.433a0c589e05079a91ea29ae7538e3be.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0028_JPG.rf.f9c6bde2b29627fca3ab55bdd7ac76c6.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0029_JPG.rf.6be501c7ec4cbf3331d698a82f98539c.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0030_JPG.rf.38fcea35bf23d8e5c8baf8beeb38d7e8.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0031_JPG.rf.1e7d66efb0c453fb0b3e7a5a37da3156.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0041_JPG.rf.8d70d52eabd4003e637f601d15b90773.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0048_JPG.rf.f12249276f697f1f7ab9a89f4441e78d.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0054_JPG.rf.64f6afd355a3d390e0e601d48b251f07.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0056_JPG.rf.024e0a9566a694d12d5df24e1831df4f.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0060_JPG.rf.a021e36a66c062fd922254bad3ec7239.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0061_JPG.rf.d309384f424b3b6df1683bf0f52261a3.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0065_JPG.rf.ac8c4e5a082b21163002a5fae9043bdb.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0076_JPG.rf.5b94beed18295525e53f8e9379a339f4.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0089_JPG.rf.f0e4679985c658cbd2661378016ec303.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0093_JPG.rf.956288ae5c025d681f36bcf95a69536e.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0094_JPG.rf.0a049e4a3a314eacc3c16e9b867b3733.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0081_0099_JPG.rf.b3d4970f431e86fc703c28d277de04b5.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0004_JPG.rf.df403e0e6048ac3397400af13e43ab43.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0006_JPG.rf.02eba7ddb8f0a0fa35bb0fefd2b0d7b0.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0013_JPG.rf.71e5b945e6685f6e846e5c53aef9996b.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0018_JPG.rf.9b13f0402ab39bb282ba6e9cdc3cb0e0.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0033_JPG.rf.2672b343c2a0d5abe0cfc27e56b12478.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0036_JPG.rf.b56497ead353995643cf708b9b1ce524.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0037_JPG.rf.03fd7f6b97f6548070362ce9d227751e.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0128_0048_JPG.rf.307acc098f47413dad4de3e32f20d083.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0002_JPG.rf.410c871e3a49680f3891ae172f2bcc05.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0005_JPG.rf.31fb7367673f884c7b48001a1759ae9d.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0008_JPG.rf.8cce59520cba1e17a02ff22c23898fb4.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0010_JPG.rf.87f83bfe330d3f2f7c74cf16172acebc.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0013_JPG.rf.e1aa7907bedfdb1157c05d91f54858f7.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0024_JPG.rf.a06724e040fbd707c2b83f1f5b98a731.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0028_JPG.rf.b70fc5321e3c7df40636650d1fced395.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0032_JPG.rf.a08578f6ad045cc24df943e753813737.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0040_JPG.rf.84aef3583901a159295d8df160dd9500.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0042_JPG.rf.033b57c212c56685372452a66d65dd46.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0043_JPG.rf.527aa04bd9201b0bdd53398f983410ac.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0044_JPG.rf.8410683b8ab60731c39be7eb78c4b163.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0047_JPG.rf.7ad574812fbb591b2f102effb5d694fe.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/101_0129_0048_JPG.rf.9bf8570e92f3423ed07156f830cd0f27.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/Boetie_png.rf.94653ffe15c836d7e39c8ac3a474f8d1.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/Chauchat_png.rf.6c5124cc9ea1b3685908d3f81fb1a8af.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/D37103-C102827-MONTPARNASSE_png.rf.908a345ea001b7f4160b08ea3003e248.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/D42495_APHP_CC49_png.rf.f96732d988d50c04335f240da40bb0b0.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/DOMINIQUE_png.rf.ea4adb5fff7f252e1cf8d0b1d20aff3a.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/FOCH_png.rf.cc078cf1e5c525c89d6cedf47891e997.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/FRIEDLAND-CC49_png.rf.d1c3e3aadd774a697071cba8c5a18c0f.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/LAVOISIER-CC49_png.rf.4b6337a3aad9da858a48067bca712185.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/ORTHOPHOTO_png.rf.7ed33c133c1caabec30bcf982495da03.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/REAUMUR_png.rf.b58441e40b39674c789800ca919badf5.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/TOITURE_png.rf.0eee8d2cb5b73ac00a06033e4ef43199.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/Toiture_Malakoff_png.rf.72bbe070f92a0183f1a8c2c4b114269b.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: WARNING: ../datasets/roboflow/train/images/Toiture_rue_pavee_png.rf.71ea53d3bec0983834c574eef71e765a.jpg: ignoring corrupt image/label: The DType <class 'numpy._IntegerAbstractDType'> could not be promoted by <class 'numpy.dtypes.StrDType'>. This means that no common DType exists for the given inputs. For example they cannot be stored in a single array unless the dtype is
object. The full list of DTypes is: (<class 'numpy._IntegerAbstractDType'>, <class 'numpy.dtypes.StrDType'>)train: New cache created: ../datasets/roboflow/train/labelTxt.cache
Traceback (most recent call last):
File "/content/yolov5_obb/train.py", line 633, in
main(opt)
File "/content/yolov5_obb/train.py", line 530, in main
train(opt.hyp, opt, device, callbacks)
File "/content/yolov5_obb/train.py", line 213, in train
train_loader, dataset = create_dataloader(train_path, imgsz, batch_size // WORLD_SIZE, gs, names, single_cls,
File "/content/yolov5_obb/utils/datasets.py", line 101, in create_dataloader
dataset = LoadImagesAndLabels(path, names, imgsz, batch_size,
File "/content/yolov5_obb/utils/datasets.py", line 444, in init
labels, shapes, self.segments = zip(*cache.values())
ValueError: not enough values to unpack (expected 3, got 0)
The text was updated successfully, but these errors were encountered: