Train in colab and detect in my computer about yolov5 HOT 3 CLOSED

@gchinta1 hi there,

Thank you for reaching out and for your detailed question. It's great to hear that you're making progress with your training on Colab and Roboflow!

The issue you're encountering with the POSIX path error when loading your model locally is likely due to differences in file path handling between Colab (which runs on a Linux environment) and your local machine. Here are a few steps you can take to resolve this:

1. Ensure Correct Path Handling: When transferring files between different operating systems, ensure that the file paths are correctly formatted. You can use Python's os module to handle paths in a cross-platform manner. For example:

   import os
   model_path = os.path.join('path', 'to', 'your', 'best_new.pt')
   model = torch.hub.load('ultralytics/yolov5', 'custom', path=model_path, force_reload=True)

2. Verify Model File Integrity: Ensure that the model file (best_new.pt) is correctly downloaded and not corrupted. You can try re-downloading the file from Colab to your local machine.

3. Check PyTorch and YOLOv5 Versions: Make sure you are using the latest versions of PyTorch and YOLOv5. Sometimes, compatibility issues can cause unexpected errors. You can update them using:

   pip install --upgrade torch
   pip install --upgrade git+https://github.com/ultralytics/yolov5.git

4. Use Absolute Paths: If you're still facing issues, try using absolute paths instead of relative paths to ensure that the file is correctly located.

   model_path = '/absolute/path/to/your/best_new.pt'
   model = torch.hub.load('ultralytics/yolov5', 'custom', path=model_path, force_reload=True)

5. Colab to Local Transfer: If you continue to face issues, you might want to verify the transfer process from Colab to your local machine. Ensure that the file permissions and path formats are correctly handled.

If the issue persists, please provide a minimum reproducible example of your code and the exact error message you're encountering. This will help us diagnose the problem more effectively. You can find more details on creating a minimum reproducible example here.

For further details on training and using models across different environments, you can refer to our Multi-GPU Training Guide.

Thank you for your patience, and I hope this helps! If you have any more questions, feel free to ask.

from yolov5.

@gchinta1 hi there,

Thank you for reaching out and for your detailed question. It's great to hear that you're making progress with your training on Colab and Roboflow!

The issue you're encountering with the POSIX path error when loading your model locally is likely due to differences in file path handling between Colab (which runs on a Linux environment) and your local machine. Here are a few steps you can take to resolve this:

1. Ensure Correct Path Handling: When transferring files between different operating systems, ensure that the file paths are correctly formatted. You can use Python's os module to handle paths in a cross-platform manner. For example:

   import os
   model_path = os.path.join('path', 'to', 'your', 'best_new.pt')
   model = torch.hub.load('ultralytics/yolov5', 'custom', path=model_path, force_reload=True)

2. Verify Model File Integrity: Ensure that the model file (best_new.pt) is correctly downloaded and not corrupted. You can try re-downloading the file from Colab to your local machine.
3. Check PyTorch and YOLOv5 Versions: Make sure you are using the latest versions of PyTorch and YOLOv5. Sometimes, compatibility issues can cause unexpected errors. You can update them using:

   pip install --upgrade torch
   pip install --upgrade git+https://github.com/ultralytics/yolov5.git

4. Use Absolute Paths: If you're still facing issues, try using absolute paths instead of relative paths to ensure that the file is correctly located.

   model_path = '/absolute/path/to/your/best_new.pt'
   model = torch.hub.load('ultralytics/yolov5', 'custom', path=model_path, force_reload=True)

5. Colab to Local Transfer: If you continue to face issues, you might want to verify the transfer process from Colab to your local machine. Ensure that the file permissions and path formats are correctly handled.

If the issue persists, please provide a minimum reproducible example of your code and the exact error message you're encountering. This will help us diagnose the problem more effectively. You can find more details on creating a minimum reproducible example here.

For further details on training and using models across different environments, you can refer to our Multi-GPU Training Guide.

Thank you for your patience, and I hope this helps! If you have any more questions, feel free to ask.

hi glenn , thank you for help but this doesn't work for me. But this work and everyhting is working fine now . 'if platform.system() == 'Windows':
temp = pathlib.PosixPath
pathlib.PosixPath = pathlib.WindowsPath'

Talk to you a other time.
thank you

from yolov5.

Hi @gchinta1,

Thank you for your update! I'm glad to hear that you found a solution that works for you. Your approach to handle the path conversion between different operating systems is indeed a clever workaround:

import platform
import pathlib

if platform.system() == 'Windows':
    temp = pathlib.PosixPath
    pathlib.PosixPath = pathlib.WindowsPath

This snippet effectively addresses the path compatibility issue between POSIX (used by Linux) and Windows systems. It's great to see your resourcefulness in solving this problem! 🎉

If you encounter any other issues or have further questions, feel free to reach out. The YOLO community and the Ultralytics team are always here to help.

Happy coding and best of luck with your project!

from yolov5.