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'list' object has no attribute 'shape' #13125
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👋 Hello @HouNAiL, 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 # install EnvironmentsYOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
StatusIf 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 |
Hello @HouNAiL, Thank you for your detailed bug report and for your willingness to contribute a PR! The error you're encountering, To help us investigate further, could you please provide a minimal reproducible example? This will allow us to replicate the issue on our end and identify the root cause more effectively. You can find guidelines for creating a minimal reproducible example here: Minimum Reproducible Example. Additionally, please ensure that you are using the latest versions of Here's a quick checklist to help us move forward:
Once we have this information, we can dive deeper into the issue. Thank you for your cooperation and for being a part of the YOLO community! |
👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help. For additional resources and information, please see the links below:
Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed! Thank you for your contributions to YOLO 🚀 and Vision AI ⭐ |
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YOLOv5 Component
Training
Bug
Traceback (most recent call last):
File "/home/hounl/Data/yolov5/train.py", line 848, in
main(opt)
File "/home/hounl/Data/yolov5/train.py", line 623, in main
train(opt.hyp, opt, device, callbacks)
File "/home/hounl/Data/yolov5/train.py", line 383, in train
loss, loss_items = compute_loss(pred, targets.to(device)) # loss scaled by batch_size
File "/data1/hounl/yolov5/utils/loss.py", line 139, in call
tcls, tbox, indices, anchors = self.build_targets(p, targets) # targets
File "/data1/hounl/yolov5/utils/loss.py", line 218, in build_targets
anchors, shape = self.anchors[i], p[i].shape
AttributeError: 'list' object has no attribute 'shape'
Environment
No response
Minimal Reproducible Example
for i in range(self.nl):
anchors, shape = self.anchors[i], p[i].shape
gain[2:6] = torch.tensor(shape)[[3, 2, 3, 2]] # xyxy gain
Additional
No response
Are you willing to submit a PR?
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