Comments (2)
👋 Hello @zmtttt, 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 # install
Environments
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
from yolov5.
Hey there! 😊 It looks like you're encountering an issue with FP16 inference using TensorRT and encountered a _pickle.UnpicklingError
. This error typically happens when there is an issue with the file being loaded, such as the file being corrupted or not fully downloaded.
In your case, the error during loading the .onnx
model file suggests that the file might be corrupted or incomplete.
Here's a quick suggestion to try:
- Double-check if the
.onnx
model file is completely downloaded and is not corrupted. You might want to re-download the file or ensure it was correctly generated. - Ensure your environment is properly set up for exporting models with TensorRT and your PyTorch, and TensorRT installations are compatible and up to date.
If the issue persists after trying these steps, please provide more details, including the exact command you're using to generate the .onnx
file, and we'll be happy to take another look. 🚀
For more guidance, the Ultralytics Docs have additional info and troubleshooting tips that might help.
from yolov5.
Related Issues (20)
- Error loading self trained model HOT 4
- Image not found error HOT 1
- RuntimeError: Sizes of tensors must match except in dimension 1. Expected size 16 but got size 32 for tensor number 1 in the list. HOT 1
- How to do instance segmention on video or streaming data HOT 2
- Multi-GPU train HOT 1
- No labels in D:\yolov5\datasets\img\train.cache. Can not train without labels HOT 2
- Manual Execution HOT 2
- Add ghost modules into tf.py for exporting yolov5s-ghost.pt to tensorflow saved_model or tflite HOT 2
- polygon annotation to object detection HOT 1
- The prediction of Yolov5 HOT 2
- yolo:latest image opencv waiting "xcb" code error? HOT 15
- Similar Dataloader in yolov5 HOT 3
- Regarding predictions of yolov5 HOT 5
- Example "detect.py" get somesthing wrong HOT 3
- Extremely low precision but high mAP HOT 2
- Can yolov5 use as a part of commercial project , if so do we need to open-source the code or the whole project ? HOT 8
- ValueError: not enough values to unpack (expected 3, got 0) YOLOv5_obb HOT 5
- 提升训练速度 HOT 1
- is there a max limit to --imgsz ? HOT 6
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