Comments (4)
@LordSizzz, I'm glad to hear that the solution worked for you! If you have any more questions or run into other issues, feel free to reach out. Happy coding! π
from ultralytics.
π Hello @LordSizzz, thank you for your interest in Ultralytics YOLOv8 π! We recommend a visit to the Docs for new users where you can find many Python and CLI usage examples and where many of the most common questions may already be answered.
If this is a π Bug Report, please provide a minimum reproducible example to help us debug it.
If this is a custom training β Question, please provide as much information as possible, including dataset image examples and training logs, and verify you are following our Tips for Best Training Results.
Join the vibrant Ultralytics Discord π§ community for real-time conversations and collaborations. This platform offers a perfect space to inquire, showcase your work, and connect with fellow Ultralytics users.
Install
Pip install the ultralytics
package including all requirements in a Python>=3.8 environment with PyTorch>=1.8.
pip install ultralytics
Environments
YOLOv8 may be run in any of the following up-to-date verified environments (with all dependencies including CUDA/CUDNN, Python and PyTorch preinstalled):
- 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 Ultralytics CI tests are currently passing. CI tests verify correct operation of all YOLOv8 Modes and Tasks on macOS, Windows, and Ubuntu every 24 hours and on every commit.
from ultralytics.
@LordSizzz hello,
Thank you for providing detailed information about the issue you're encountering with ONNX and multiple RTSP streams. The error message you're seeing suggests that there's a mismatch in the expected input dimensions for your model. The ONNX model is expecting a single input stream (batch size of 1), but it seems to be receiving multiple streams simultaneously (batch size of 6).
This can occur if the model was exported with a specific batch size that doesn't match the number of streams you're trying to process. Here are a couple of steps you can take to resolve this:
-
Re-export the Model with Dynamic Axes: When exporting your model to ONNX, ensure that you enable dynamic axes to allow for variable batch sizes. This can be done by setting the
dynamic=True
parameter in themodel.export()
function. This will allow the model to handle varying numbers of input streams. -
Adjust the Input Feed: Ensure that the input to the model is correctly batched according to the model's expected input dimensions. If your model expects a batch size of 1, you might need to process each stream individually or modify the model to accept the actual number of streams you intend to use.
Here's an example of how you might adjust the export code:
model.export(format="onnx", dynamic=True)
Please try these adjustments and let us know if the issue persists. We're here to help!
from ultralytics.
@glenn-jocher thank you for the quick response, what you just mentioned whas indeed the issue, due to my lack of knowledge and the fact that it worked just before the conversion caused me to think that, so yes, adding ,dynamic=True
in the export code did fix my problem, thank you for your help.
from ultralytics.
Related Issues (20)
- Installing Ultralytics with system installed matplotlib - cannot import name 'rcParams' ifrom matplotlib,axes(in python_path.) HOT 1
- Clarification on GPL License Usage in Closed-Source Projects HOT 2
- Mixup augmentation cancels mosaic augmentation. HOT 4
- a question about trainer.py HOT 1
- About pretrained YOLO models HOT 3
- question about yolo-world default text features? HOT 9
- Custom Checkpoints not working with SAM HOT 8
- May I ask if the model can still eliminate NMS if I change the v10Detect detection head to another detection headοΌ HOT 2
- Running exe using Ultralytics YOLOv8 packaged with pyinstaller causing WMIC popup command prompts on Windows HOT 4
- Segment object has no attribute detect HOT 2
- Can we use hyperspectral image of 268 bands for training using yolov8x HOT 2
- How to use a freezed pretrained backone and train head from scratch? Am I doing right? HOT 3
- Yolov5 with Cvzone hand Detector Module HOT 5
- Hello author, while using OBB to train my dataset, I found that the tilted boxes in the validation set images and training set images after training did not match. There were cases where the angles were skewed, and during my inference, the detection boxes were completely different from what I labeled HOT 18
- Filter out detection below 0.70 confidence level on YOLO v8 OBB
- how can i improve the accuracy of yolov8 on custom model HOT 2
- Using the model that trained on my own dataset as pretrained is sense? HOT 1
- change the map50-95 criteria to map50-75 HOT 4
- MULTI GPU TRAINING not working with pretrained weights HOT 19
- YOLOv8 : pose(person) + object detection or classification(other object) HOT 7
Recommend Projects
-
React
A declarative, efficient, and flexible JavaScript library for building user interfaces.
-
Vue.js
π Vue.js is a progressive, incrementally-adoptable JavaScript framework for building UI on the web.
-
Typescript
TypeScript is a superset of JavaScript that compiles to clean JavaScript output.
-
TensorFlow
An Open Source Machine Learning Framework for Everyone
-
Django
The Web framework for perfectionists with deadlines.
-
Laravel
A PHP framework for web artisans
-
D3
Bring data to life with SVG, Canvas and HTML. πππ
-
Recommend Topics
-
javascript
JavaScript (JS) is a lightweight interpreted programming language with first-class functions.
-
web
Some thing interesting about web. New door for the world.
-
server
A server is a program made to process requests and deliver data to clients.
-
Machine learning
Machine learning is a way of modeling and interpreting data that allows a piece of software to respond intelligently.
-
Visualization
Some thing interesting about visualization, use data art
-
Game
Some thing interesting about game, make everyone happy.
Recommend Org
-
Facebook
We are working to build community through open source technology. NB: members must have two-factor auth.
-
Microsoft
Open source projects and samples from Microsoft.
-
Google
Google β€οΈ Open Source for everyone.
-
Alibaba
Alibaba Open Source for everyone
-
D3
Data-Driven Documents codes.
-
Tencent
China tencent open source team.
from ultralytics.