when i using detect.py in win10! File "\general.py", line 484, in non_max_suppression nc = prediction.shape[2] - 5 # number of classes IndexError: tuple index out of range

[whiteless9]

❔Question

Additional context

[github-actions[bot]]

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[glenn-jocher]

@whiteless9 👋 hi, thanks for letting us know about this problem with YOLOv5 🚀. We've created a few short guidelines below to help users provide what we need in order to get started investigating a possible problem.

How to create a Minimal, Reproducible Example

When asking a question, people will be better able to provide help if you provide code that they can easily understand and use to reproduce the problem. This is referred to by community members as creating a minimum reproducible example. Your code that reproduces the problem should be:

• ✅ Minimal – Use as little code as possible that still produces the same problem
• ✅ Complete – Provide all parts someone else needs to reproduce your problem in the question itself
• ✅ Reproducible – Test the code you're about to provide to make sure it reproduces the problem

In addition to the above requirements, for Ultralytics to provide assistance your code should be:

• ✅ Current – Verify that your code is up-to-date with current GitHub master, and if necessary git pull or git clone a new copy to ensure your problem has not already been resolved by previous commits.
• ✅ Unmodified – Your problem must be reproducible without any modifications to the codebase in this repository. Ultralytics does not provide support for custom code ⚠️.

If you believe your problem meets all of the above criteria, please close this issue and raise a new one using the 🐛 Bug Report template and providing a minimum reproducible example to help us better understand and diagnose your problem.

Thank you! 😃

[Hezhexi2002]

I meet the same error and it works well before,I don't know what happened

[glenn-jocher]

@Hezhexi2002 👋 hi, thanks for letting us know about this problem with YOLOv5 🚀. We've created a few short guidelines below to help users provide what we need in order to get started investigating a possible problem.

How to create a Minimal, Reproducible Example

When asking a question, people will be better able to provide help if you provide code that they can easily understand and use to reproduce the problem. This is referred to by community members as creating a minimum reproducible example. Your code that reproduces the problem should be:

• ✅ Minimal – Use as little code as possible that still produces the same problem
• ✅ Complete – Provide all parts someone else needs to reproduce your problem in the question itself
• ✅ Reproducible – Test the code you're about to provide to make sure it reproduces the problem

In addition to the above requirements, for Ultralytics to provide assistance your code should be:

• ✅ Current – Verify that your code is up-to-date with current GitHub master, and if necessary git pull or git clone a new copy to ensure your problem has not already been resolved by previous commits.
• ✅ Unmodified – Your problem must be reproducible without any modifications to the codebase in this repository. Ultralytics does not provide support for custom code ⚠️.

If you believe your problem meets all of the above criteria, please close this issue and raise a new one using the 🐛 Bug Report template and providing a minimum reproducible example to help us better understand and diagnose your problem.

Thank you! 😃

[github-actions[bot]]

👋 Hello, this issue has been automatically marked as stale because it has not had recent activity. Please note it will be closed if no further activity occurs.

Access additional YOLOv5 🚀 resources:

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[Alek-dr]

@whiteless9 I got same error after git pool Fix - add dim before nms:

pred = torch.unsqueeze(pred, 0)

pred = non_max_suppression(pred, conf_thres, iou_thres, classes, agnostic_nms, max_det=max_det)

[RoyCopter]

@Alek-dr @glenn-jocher I had the same problem using YOLOv5 v6.1 with my custom code. (I did everything that required like the original code, but for some reason it throw that error).

after adding

pred = torch.unsqueeze(pred, 0)

it solved as @Alek-dr said.

thanks!

[glenn-jocher]

@whiteless9 @Alek-dr @RoyCopter can you help us by supplying a reproducible example that we can use to view the error ourselves?

[FaragSeif]

@glenn-jocher I'm having the same issue, also using Windows 10. Here is the minimum reproducible code:

import numpy as np
import yolov5
from yolov5.utils.general import non_max_suppression

model = yolov5.load("./yolov5s.pt")

results = model(np.zeros((3, 640, 640)))
pred = results.pred[0]
print(non_max_suppression(pred))

It throws the following error:

Traceback (most recent call last):
  File "yolo_test.py", line 9, in <module>
    print(non_max_suppression(pred))
  File "venv\lib\site-packages\yolov5\utils\general.py", line 1055, in non_max_suppression
    nc = prediction.shape[2] - nm - 5  # number of classes
IndexError: tuple index out of range

Am I perhaps using it incorrectly?

[glenn-jocher]

@SeifAbdElrhman 👋 Hello! Thanks for asking about handling inference results. YOLOv5 🚀 PyTorch Hub models allow for simple model loading and inference in a pure python environment without using detect.py.

Simple Inference Example

This example loads a pretrained YOLOv5s model from PyTorch Hub as model and passes an image for inference. 'yolov5s' is the YOLOv5 'small' model. For details on all available models please see the README. Custom models can also be loaded, including custom trained PyTorch models and their exported variants, i.e. ONNX, TensorRT, TensorFlow, OpenVINO YOLOv5 models.

import torch

# Model
model = torch.hub.load('ultralytics/yolov5', 'yolov5s')  # yolov5n - yolov5x6 official model
#                                            'custom', 'path/to/best.pt')  # custom model

# Images
im = 'https://ultralytics.com/images/zidane.jpg'  # or file, Path, URL, PIL, OpenCV, numpy, list

# Inference
results = model(im)

# Results
results.print()  # or .show(), .save(), .crop(), .pandas(), etc.
results.xyxy[0]  # im predictions (tensor)

results.pandas().xyxy[0]  # im predictions (pandas)
#      xmin    ymin    xmax   ymax  confidence  class    name
# 0  749.50   43.50  1148.0  704.5    0.874023      0  person
# 2  114.75  195.75  1095.0  708.0    0.624512      0  person
# 3  986.00  304.00  1028.0  420.0    0.286865     27     tie

results.pandas().xyxy[0].value_counts('name')  # class counts (pandas)
# person    2
# tie       1

See YOLOv5 PyTorch Hub Tutorial for details.

Good luck 🍀 and let us know if you have any other questions!

[SuperMaximus1984]

Same error here. Appeared all of a sudden in the loop if inferences (same source). What may it be?

Traceback (most recent call last):
  File "/home/max/yolov5-flask/camdetect.py", line 56, in <module>
    results = model('http://192.168.0.6/jpg/1/image.jpg', size=2688)
  File "/usr/local/lib/python3.8/dist-packages/torch/nn/modules/module.py", line 889, in _call_impl
    result = self.forward(*input, **kwargs)
  File "/usr/local/lib/python3.8/dist-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
    return func(*args, **kwargs)
  File "/root/.cache/torch/hub/ultralytics_yolov5_master/models/common.py", line 689, in forward
    if im.shape[0] < 5:  # image in CHW
IndexError: tuple index out of range

[glenn-jocher]

@SuperMaximus1984 👋 hi, thanks for letting us know about this possible problem with YOLOv5 🚀. We've created a few short guidelines below to help users provide what we need in order to start investigating a possible problem.

How to create a Minimal, Reproducible Example

When asking a question, people will be better able to provide help if you provide code that they can easily understand and use to reproduce the problem. This is referred to by community members as creating a minimum reproducible example. Your code that reproduces the problem should be:

• ✅ Minimal – Use as little code as possible to produce the problem
• ✅ Complete – Provide all parts someone else needs to reproduce the problem
• ✅ Reproducible – Test the code you're about to provide to make sure it reproduces the problem

For Ultralytics to provide assistance your code should also be:

• ✅ Current – Verify that your code is up-to-date with GitHub master, and if necessary git pull or git clone a new copy to ensure your problem has not already been solved in master.
• ✅ Unmodified – Your problem must be reproducible using official YOLOv5 code without changes. Ultralytics does not provide support for custom code ⚠️.

If you believe your problem meets all the above criteria, please close this issue and raise a new one using the 🐛 Bug Report template with a minimum reproducible example to help us better understand and diagnose your problem.

Thank you! 😃

[nolby003]

I am opening this back up as this is not resolved. I classified using Yolov8, but I am using Yolov5 to detect , and getting this same error, could it be that Yolov8 generates a weight incompatible with yolov5?

[glenn-jocher]

It's likely that YOLOv8 weights are incompatible with YOLOv5. Please ensure you use YOLOv5-trained weights with YOLOv5 models.