Comments (2)
π Hello @lzmz08, thank you for your interest in YOLOv5 π! Please visit our βοΈ 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 π Bug Report, please provide screenshots and minimum viable code to reproduce your issue, otherwise we can not help you.
If this is a custom training β Question, please provide as much information as possible, including dataset images, training logs, screenshots, and a public link to online W&B logging if available.
For business inquiries or professional support requests please visit https://ultralytics.com or email Glenn Jocher at [email protected].
Requirements
Python>=3.6.0 with all requirements.txt installed including PyTorch>=1.7. To get started:
$ git clone https://github.com/ultralytics/yolov5
$ cd yolov5
$ pip install -r requirements.txt
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):
- Google Colab and Kaggle 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 (train.py), validation (val.py), inference (detect.py) and export (export.py) on MacOS, Windows, and Ubuntu every 24 hours and on every commit.
from quantized-yolov5.
Hi,
We used only quantized Yolov1 in our experiments. But, you can replace Yolov5's layers with Quantized alternatives, and use our repository for training it.
from quantized-yolov5.
Related Issues (9)
- Quantised YOLOv5 HOT 19
- Result reproduction HOT 5
- Can the quantized yolov5 model with Brevitas be deployed on the DPU (Deep Learning Processing Unit)? HOT 2
- Supported FINN layers HOT 3
- Some error in export to onnx HOT 5
- RuntimeError: Expected all tensors to be on the same device, but found at least two devices, cuda:0 and cpu! HOT 2
- Achieving FPS mentioned in LPYOLO Paper HOT 1
- Question about which version of YOLO used HOT 1
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from quantized-yolov5.