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Using .onnx file for the test, all the metrics are 0(There is no problem with using .pt files) #9012
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👋 Hello @DiKu-nn, 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 screenshots and minimum viable code to reproduce your issue, otherwise we can not help you. If this is a custom training ❓ 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 support@ultralytics.com. RequirementsPython>=3.7.0 with all requirements.txt installed including PyTorch>=1.7. 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 (train.py), validation (val.py), inference (detect.py) and export (export.py) on macOS, Windows, and Ubuntu every 24 hours and on every commit. |
i only take one of yolohead for output |
@DiKu-nn 👋 Hello! Thanks for asking about YOLOv5 🚀 benchmarks. YOLOv5 inference is officially supported in 11 formats, and all formats are benchmarked for identical accuracy and to compare speed every 24 hours by the YOLOv5 CI. 💡 ProTip: Export to ONNX or OpenVINO for up to 3x CPU speedup. See CPU Benchmarks.
BenchmarksBenchmarks below run on a Colab Pro with the YOLOv5 tutorial notebook . To reproduce: python utils/benchmarks.py --weights yolov5s.pt --imgsz 640 --device 0 Colab Pro V100 GPU
Colab Pro CPU
Good luck 🍀 and let us know if you have any other questions! |
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Using .onnx file for the test, all the metrics are 0 (There is no problem with using .pt files)
Class Images Labels P R mAP@.5 mAP@.5:.95: 100%|██████████| 253/253 [00:52<00:00, 4.85it/s]
all 253 0 0 0 0 0
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