AssertionError: 1/1: 0... Failed to open 0

[deb-cod]

Search before asking

• I have searched the YOLOv5 issues and found no similar bug report.

YOLOv5 Component

No response

Bug

Fusing layers...
YOLOv5x summary: 444 layers, 86173414 parameters, 0 gradients
WARNING: Environment does not support cv2.imshow() or PIL Image.show() image displays
cv2.imshow() is disabled in Google Colab environments
[ WARN:0] global /io/opencv/modules/videoio/src/cap_v4l.cpp (802) open VIDEOIO ERROR: V4L: can't open camera by index 0
Traceback (most recent call last):
File "/content/yolov5/detect.py", line 252, in
main(opt)
File "/content/yolov5/detect.py", line 247, in main
run(**vars(opt))
File "/usr/local/lib/python3.7/dist-packages/torch/autograd/grad_mode.py", line 27, in decorate_context
return func(*args, **kwargs)
File "/content/yolov5/detect.py", line 100, in run
dataset = LoadStreams(source, img_size=imgsz, stride=stride, auto=pt)
File "/content/yolov5/utils/dataloaders.py", line 325, in init
assert cap.isOpened(), f'{st}Failed to open {s}'
AssertionError: 1/1: 0... Failed to open 0

Environment

detect: weights=['/content/yolov5/best.pt'], source=0, data=/content/yolov5/data/fire.yaml, imgsz=[640, 640], conf_thres=0.25, iou_thres=0.45, max_det=1000, device=, view_img=False, save_txt=False, save_conf=False, save_crop=False, nosave=False, classes=None, agnostic_nms=False, augment=False, visualize=False, update=False, project=yolov5/runs/detect, name=exp, exist_ok=False, line_thickness=3, hide_labels=False, hide_conf=False, half=False, dnn=False
YOLOv5 🚀 v6.1-251-gc23a441 Python-3.7.13 torch-1.11.0+cu113 CUDA:0 (Tesla P100-PCIE-16GB, 16281MiB)

I ran in terminal in Colab... still getting the same problem

Minimal Reproducible Example

I ran in terminal in Colab... still getting the same problem

Additional

No response

Are you willing to submit a PR?

• Yes I'd like to help by submitting a PR!

[github-actions]

👋 Hello @deb-cod, 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 [email protected].

Requirements

Python>=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

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.

[glenn-jocher]

@deb-cod webcam inference is only supported on local devices. I’ll add a TODO to improve error reporting on this to make it clearer for users

[glenn-jocher]

@deb-cod good news 😃! Your original issue may now be fixed ✅ in PR #8209. This PR adds improved error reporting to help users understand that webcam inference with --source 0 must be run in a local environment with access to a webcam, not on remote environments like Colab/Kaggle.

To receive this update:

• Git – git pull from within your yolov5/ directory or git clone https://github.com/ultralytics/yolov5 again
• PyTorch Hub – Force-reload model = torch.hub.load('ultralytics/yolov5', 'yolov5s', force_reload=True)
• Notebooks – View updated notebooks
• Docker – sudo docker pull ultralytics/yolov5:latest to update your image

Thank you for spotting this issue and informing us of the problem. Please let us know if this update resolves the issue for you, and feel free to inform us of any other issues you discover or feature requests that come to mind. Happy trainings with YOLOv5 🚀!

[banana7778]

same question..didU solved it？

[sloika]

I try to use it locally on my machine and it still has the same bug. Already up to date repo.

[glenn-jocher]

Webcam inference works correctly: