Comments (3)
👋 Hello @Anchal123Kumar, thank you for your interest in Ultralytics YOLOv8 🚀! 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 🐛 Bug Report, please provide a minimum reproducible example to help us debug it.
If this is a custom training ❓ 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.
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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.
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Hello! It looks like you're trying to train an instance segmentation model but the code is loading a detection model instead. To train a segmentation model, you should use a segmentation model file, like yolov8n-seg.pt
, instead of yolov8n.pt
.
Here's a corrected version of your code:
from ultralytics import YOLO
def main():
# Ensure you're using a segmentation model
model = YOLO("D:\\AI\\Mars\\interface scrub\\yolov8n-seg.pt")
results = model.train(
data="D:\\AI\\Mars\\interface scrub\\Data\\data.yaml",
imgsz=640,
epochs=130,
batch=30,
name="Office_Senitize15",
task="segment"
)
if __name__ == '__main__':
main()
Make sure that yolov8n-seg.pt
is correctly placed in your specified directory or adjust the path accordingly. This should resolve the issue of downloading the wrong model and ensure you're training with the correct segmentation model. Happy training! 🚀
from ultralytics.
👋 Hello there! We wanted to give you a friendly reminder that this issue has not had any recent activity and may be closed soon, but don't worry - you can always reopen it if needed. If you still have any questions or concerns, please feel free to let us know how we can help.
For additional resources and information, please see the links below:
- Docs: https://docs.ultralytics.com
- HUB: https://hub.ultralytics.com
- Community: https://community.ultralytics.com
Feel free to inform us of any other issues you discover or feature requests that come to mind in the future. Pull Requests (PRs) are also always welcomed!
Thank you for your contributions to YOLO 🚀 and Vision AI ⭐
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Related Issues (20)
- Parameters in C2f and issues with logging output HOT 1
- YOLOv10 predict has wrong postprocess. HOT 1
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- AttributeError: Can't get attribute 'v10DetectLoss' on <module 'ultralytics.utils.loss' from '/usr/local/lib/python3.10/dist-packages/ultralytics/utils/loss.py'> HOT 1
- How to make Yolov8-segmatation model convert to tensor-RT INT8 model? HOT 1
- Proper CoreML Conversion for YOLOv10 HOT 2
- agnostic_nms=True is not working in yolov8-obb HOT 6
- Make Enough FPS with Multiple Models for Multiple Stream HOT 2
- TensorRT Export Method Restricts Workspace Memory to 4GB HOT 3
- Fast computation methods in yolov8 tracking HOT 5
- Method for Validation Using a Custom Dataset Exported from CVAT HOT 3
- Train custom Dataset with fixed H:480 but different Width: 600 - 850 HOT 1
- How to use YOLOV8-OBB on deepstream HOT 5
- After adding post-processing to the model output, repackage and export the new model HOT 1
- In the segmentation task training process, where can I find codes to draw and fill polygons from labels onto images? HOT 1
- In the segmentation task, the self-made data labels have accurate true value contours, but the contours are not accurate during training HOT 10
- Deploying the YOLOv10 model on Android using the TFLite library gives inaccurate results? HOT 7
- labeling HOT 2
- AttributeError: 'dict' object has no attribute 'box' when trying to train YOLOv10 on pytoch lightning using v10DetectLoss. HOT 3
- Can I train pose-estimation without indicating bounding box? HOT 1
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