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ultralytics 8.0.217 HUB YAML path improvements (#6556)

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Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
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Glenn Jocher 2023-11-24 15:41:10 +01:00 • committed by GitHub
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23
docs/en/guides/kfold-cross-validation.md
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@ -24,19 +24,18 @@ Without further ado, let's dive in!
- This guide assumes that annotation files are locally available.
- For our demonstration, we use the [Fruit Detection](https://www.kaggle.com/datasets/lakshaytyagi01/fruit-detection/code) dataset.
- For our demonstration, we use the [Fruit Detection](https://www.kaggle.com/datasets/lakshaytyagi01/fruit-detection/code) dataset.
- This dataset contains a total of 8479 images.
- It includes 6 class labels, each with its total instance counts listed below.
- This dataset contains a total of 8479 images.
- It includes 6 class labels, each with its total instance counts listed below.
| Class Label | Instance Count |
|:------------|:--------------:|
| Apple | 7049 |
| Grapes | 7202 |
| Pineapple | 1613 |
| Orange | 15549 |
| Banana | 3536 |
| Watermelon | 1976 |
| Class Label | Instance Count |
|:------------|:--------------:|
| Apple | 7049 |
| Grapes | 7202 |
| Pineapple | 1613 |
| Orange | 15549 |
| Banana | 3536 |
| Watermelon | 1976 |
- Necessary Python packages include:

2
docs/hi/models/sam.md
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@ -140,7 +140,7 @@ Segment Anything Model का उपयोग उपस्थित डेटा
| SAM का सबसे छोटा, SAM-b | 358 MB | 94.7 M | 51096 ms/im |
| [मोबाइल SAM](mobile-sam.md) | 40.7 MB | 10.1 M | 46122 ms/im |
| [अग्री सेगमेंटेशन वाली FastSAM-s, YOLOv8 बैकबोन सहित](fast-sam.md) | 23.7 MB | 11.8 M | 115 ms/im |
| Ultralytics [योलोवी8न-seg](../टास्क/सेगमेंट.md) | **6.7 MB** (53.4 गुना छोटा) | **3.4 M** (27.9x कम) | **59 ms/im** (866x तेज) |
| Ultralytics [योलोवी8न-seg](yolov8.md) | **6.7 MB** (53.4 गुना छोटा) | **3.4 M** (27.9x कम) | **59 ms/im** (866x तेज) |
यह तुलना मॉडल के आकार और गति में दस्तावेजीय अंतर दिखाती है। जहां SAM स्वचालित सेगमेंटेशन के लिए अद्वितीय क्षमताओं को प्रस्तुत करता है, वहीं Ultralytics विद्यमान सेगमेंटेशन मानदंडों के तुलनात्मक आकार, गति और संचालन क्षमता में समर्थन प्रदान करती है।