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unable to process the dataset #730

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BrianChen0405 opened this issue Jun 16, 2024 · 3 comments
Open
1 task done

unable to process the dataset #730

BrianChen0405 opened this issue Jun 16, 2024 · 3 comments
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question A HUB question that does not involve a bug

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@BrianChen0405
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i dont know why the ultralytics unable to process the dataset, i got train valid test and yaml in my folder

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https://drive.google.com/file/d/19HDxwDcc6Jo_ZAU5hWsymhIFAYuvsqKB/view?usp=drive_link

@BrianChen0405 BrianChen0405 added the question A HUB question that does not involve a bug label Jun 16, 2024
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👋 Hello @BrianChen0405, thank you for raising an issue about Ultralytics HUB 🚀! Please visit our HUB Docs to learn more:

  • Quickstart. Start training and deploying YOLO models with HUB in seconds.
  • Datasets: Preparing and Uploading. Learn how to prepare and upload your datasets to HUB in YOLO format.
  • Projects: Creating and Managing. Group your models into projects for improved organization.
  • Models: Training and Exporting. Train YOLOv5 and YOLOv8 models on your custom datasets and export them to various formats for deployment.
  • Integrations. Explore different integration options for your trained models, such as TensorFlow, ONNX, OpenVINO, CoreML, and PaddlePaddle.
  • Ultralytics HUB App. Learn about the Ultralytics App for iOS and Android, which allows you to run models directly on your mobile device.
    • iOS. Learn about YOLO CoreML models accelerated on Apple's Neural Engine on iPhones and iPads.
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  • Inference API. Understand how to use the Inference API for running your trained models in the cloud to generate predictions.

If this is a 🐛 Bug Report, please provide screenshots and steps to reproduce your problem to help us get started working on a fix.

If this is a ❓ Question, please provide as much information as possible, including dataset, model, environment details etc. so that we might provide the most helpful response.

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@pderrenger
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@BrianChen0405 hello,

Thank you for reaching out and providing the details about your issue. Let's work together to resolve this!

First, please ensure that your dataset is structured correctly. Your dataset directory should contain the train, val, and test folders, along with the YAML file. The YAML file should be placed inside the root directory of your dataset, and all names (YAML, directory, and ZIP) should match. For example, if your dataset is named mydataset, you should have:

mydataset/
  ├── mydataset.yaml
  ├── train/
  ├── val/
  └── test/

Next, zip your dataset directory:

zip -r mydataset.zip mydataset

Before uploading, it's a good idea to validate your dataset to ensure there are no formatting issues. You can use the following code snippet to validate your dataset:

from ultralytics.hub import check_dataset

check_dataset("path/to/mydataset.zip", task="detect")

If everything is in order, you can proceed to upload your dataset to Ultralytics HUB. Navigate to the Datasets page, click on the Upload Dataset button, and follow the prompts.

If you have already followed these steps and are still encountering issues, please ensure you are using the latest versions of torch, ultralytics, and hub-sdk. You can update your packages using:

pip install --upgrade torch ultralytics hub-sdk

If the problem persists, could you please provide a minimum reproducible example? This will help us investigate the issue more effectively. You can find more details on creating a minimum reproducible example here.

Thank you for your patience, and we look forward to resolving this issue for you. If you have any further questions, feel free to ask!

@sergiuwaxmann
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@BrianChen0405 Hello!

I just checked our system and everything works fine.

If you are having issues uploading your dataset:

  1. Follow the steps in our documentation.
    1.2. Validate your dataset locally before uploading it to Ultralytics HUB (as @pderrenger suggested).
from ultralytics.hub import check_dataset
check_dataset("path/to/dataset.zip", task="detect")
  1. Make sure you have a stable internet connection.

I suggest trying to upload a small dataset (such as COCO8) to confirm that upload works correctly.

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