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ultralytics / yolov5

YOLOv5 🚀 in PyTorch > ONNX > CoreML > TFLite
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yolov5 with matplotlib #12391

Closed qjl1244281167 closed 8 months ago

qjl1244281167 commented 10 months ago

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YOLOv5 Component

Detection

Bug

When I use detect.py, it seems that I cannot use matplotlib.pyplot as plt drawing in the main function. Although I have imported the relevant code here, I ensure that my environment is correct and the code is correct, but plt cannot Display pictures in pycharm

Environment

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Minimal Reproducible Example

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Additional

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Are you willing to submit a PR?

github-actions[bot] commented 10 months ago

👋 Hello @qjl1244281167, 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.

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glenn-jocher commented 10 months ago

@qjl1244281167 hi there! 🌟 Matplotlib can sometimes have trouble displaying images in certain environments. This may be due to PyCharm's default settings. You can resolve this issue by adding the following line before importing pyplot:

import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt

This should allow you to display images using plt.show() in PyCharm. For more information, you can also refer to our documentation at https://docs.ultralytics.com/yolov5/. Thank you for your willingness to submit a PR – your contributions are greatly appreciated!

qjl1244281167 commented 10 months ago

@qjl1244281167 hi there! 🌟 Matplotlib can sometimes have trouble displaying images in certain environments. This may be due to PyCharm's default settings. You can resolve this issue by adding the following line before importing pyplot:

import matplotlib
matplotlib.use('TkAgg')
import matplotlib.pyplot as plt

This should allow you to display images using plt.show() in PyCharm. For more information, you can also refer to our documentation at https://docs.ultralytics.com/yolov5/. Thank you for your willingness to submit a PR – your contributions are greatly appreciated! ImportError: Cannot load backend 'TkAgg' which requires the 'tk' interactive framework, as 'headless' is currently running This is the problem I'm having .I am connected to a remote interpreter on linux

glenn-jocher commented 10 months ago

@qjl1244281167 I see. It seems like the 'TkAgg' backend is not compatible with the headless environment you are running. In this case, you can try using a non-interactive backend such as 'agg' by setting it before importing pyplot:

import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt

This should allow you to display images using plt.show() in a headless environment. Remember to refer to our documentation at https://docs.ultralytics.com/yolov5/ for more information. Thank you for bringing this issue to our attention!

qjl1244281167 commented 10 months ago

@qjl1244281167 I see. It seems like the 'TkAgg' backend is not compatible with the headless environment you are running. In this case, you can try using a non-interactive backend such as 'agg' by setting it before importing pyplot:

import matplotlib
matplotlib.use('agg')
import matplotlib.pyplot as plt

This should allow you to display images using plt.show() in a headless environment. Remember to refer to our documentation at https://docs.ultralytics.com/yolov5/ for more information. Thank you for bringing this issue to our attention!

No, this has no effect. In my project, I only need to cancel the module related to yolov5 detect without making any changes, and the image of matplotlib.pyplot can be displayed successfully.

glenn-jocher commented 10 months ago

@qjl1244281167 I understand. It seems there might be some interference between the YOLOv5 detection module and matplotlib. To isolate the issue, you can try removing the YOLOv5 detection module and check if matplotlib works as expected. This might help you identify the source of the problem. Also, make sure that there are no conflicting dependencies or interference between the two. If the issue persists, please feel free to provide more details so we can further assist you. Thank you for your patience and for your willingness to help with the PR!

qjl1244281167 commented 10 months ago

@qjl1244281167我明白。看来YOLOv5检测模块和matplotlib之间可能存在一些干扰。要隔离问题，您可以尝试删除 YOLOv5 检测模块并检查 matplotlib 是否按预期工作。这可能会帮助您确定问题的根源。另外，请确保两者之间不存在冲突的依赖关系或干扰。如果问题仍然存在，请随时提供更多详细信息，以便我们进一步为您提供帮助。感谢您的耐心等待以及您愿意帮助公关！

The problem now is that I need to use detect.py to get the xyxy coordinates of the detection object. I must use detect.py, so I extracted this part as a module of my project. I don’t know what to do now. The problem is that as soon as the detected image is processed by yolov5, matplotlib will malfunction. Obviously, there must be an internal conflict between yolov5 and matplotlib.

glenn-jocher commented 10 months ago

@qjl1244281167 I see, I understand your situation better now. It seems that there might be an internal conflict between YOLOv5 and matplotlib when used together. In this case, you can consider encapsulating the parts of YOLOv5's detect.py that you need into a separate function or script, and then try running the matplotlib code separately from that function or script to prevent any interference.

If this doesn't resolve the issue, it might be helpful to reach out to the YOLOv5 community for further insights, as they might have encountered similar challenges and found effective solutions. Additionally, you can also consider raising this issue to the Ultralytics team, who are actively working on YOLOv5, for their guidance.

Thank you for your understanding and for your contribution to the community!

github-actions[bot] commented 9 months ago

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qiang92 commented 2 months ago

Add this line before plt.show() can also solve the problem. plt.switch_backend('Qt5Agg') The reason is that once you import DetectMultiBackend module, the matplotlib auto switch backend from QtAgg to agg.

qjl1244281167 commented 2 months ago

Add this line before plt.show() can also solve the problem. plt.switch_backend('Qt5Agg') The reason is that once you import DetectMultiBackend module, the matplotlib auto switch backend from QtAgg to agg.

Thanks guy, I will try it.

glenn-jocher commented 2 months ago

Hi @qjl1244281167,

Thank you for sharing your solution! It's great to hear that switching the backend with plt.switch_backend('Qt5Agg') resolves the issue. This insight about the backend switch when importing the DetectMultiBackend module is very valuable.

If you encounter any further issues or have additional questions, please don't hesitate to ask. Also, make sure you're using the latest versions of torch and YOLOv5 from https://github.com/ultralytics/yolov5 to ensure optimal performance and compatibility.

Your contributions and feedback are greatly appreciated by the entire YOLO community and the Ultralytics team! 😊