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11 months ago 👋 Hello @marco0913, 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.
Requirements
Python>=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 # installEnvironments
YOLOv5 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
- Notebooks with free GPU:
- Google Cloud Deep Learning VM. See GCP Quickstart Guide
- Amazon Deep Learning AMI. See AWS Quickstart Guide
- Docker Image. See Docker Quickstart Guide
Status
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
glenn-jocher
marco0913
Search before asking
YOLOv5 Component
No response
Bug
Epoch GPU_mem box_loss obj_loss cls_loss Instances Size 81/299 14.1G 0.01582 0.006917 0.006883 31 640: 100% 158/158 [02:21<00:00, 1.11it/s] Class Images Instances P R mAP50 mAP50-95: 100% 18/18 [00:14<00:00, 1.27it/s] all 852 970 0.958 0.943 0.976 0.866
Traceback (most recent call last): File "/content/yolov5/train.py", line 647, in
main(opt)
File "/content/yolov5/train.py", line 536, in main
train(opt.hyp, opt, device, callbacks)
File "/content/yolov5/train.py", line 291, in train
for i, (imgs, targets, paths, _) in pbar: # batch -------------------------------------------------------------
File "/usr/local/lib/python3.10/dist-packages/tqdm/std.py", line 1182, in iter
for obj in iterable:
File "/content/yolov5/utils/dataloaders.py", line 172, 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 1345, in _next_data
return self._process_data(data)
File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/dataloader.py", line 1371, in _process_data
data.reraise()
File "/usr/local/lib/python3.10/dist-packages/torch/_utils.py", line 694, in reraise
raise exception
FileNotFoundError: Caught FileNotFoundError in DataLoader worker process 4.
Original Traceback (most recent call last):
File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/worker.py", line 308, in _worker_loop
data = fetcher.fetch(index)
File "/usr/local/lib/python3.10/dist-packages/torch/utils/data/_utils/fetch.py", line 51, 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 51, in
data = [self.dataset[idx] for idx in possibly_batched_index]
File "/content/yolov5/utils/dataloaders.py", line 661, in getitem
img, labels = self.load_mosaic(index)
File "/content/yolov5/utils/dataloaders.py", line 760, in loadmosaic
img, , (h, w) = self.load_image(index)
File "/content/yolov5/utils/dataloaders.py", line 735, in load_image
im = cv2.imread(f) # BGR
File "/content/yolov5/utils/general.py", line 1100, in imread
return cv2.imdecode(np.fromfile(filename, np.uint8), flags)
FileNotFoundError: [Errno 2] No such file or directory: '/content/drive/MyDrive/dataset_yolo5_m3_2ndTraining/images/train/Cam1_27.10.2022.14.52.41.png'
but the file is definetly there..
Environment
Google Colab
No response
Minimal Reproducible Example
!python /content/yolov5/train.py --data /content/drive/MyDrive/dataset_yolov5/config.yaml --epochs 300 --weights '' --cfg yolov5l.yaml --batch-size 24
Additional
No response
Are you willing to submit a PR?