Chiebot-Mirror
/
ultralytics
mirror of https://github.com/ultralytics/ultralytics.git
9
0
Fork 1
Code Issues Packages Projects Releases Wiki Activity

Update docs building code (#7601)

Browse Source 
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
Co-authored-by: Muhammad Rizwan Munawar <chr043416@gmail.com>
Co-authored-by: Muhammad Rizwan Munawar <muhammadrizwanmunawar123@gmail.com>
Co-authored-by: UltralyticsAssistant <web@ultralytics.com>
pull/7580/head
Glenn Jocher 1 year ago committed by GitHub
parent 5f5f5d08f2
commit d021524e85
No known key found for this signature in database
GPG Key ID: B5690EEEBB952194
9 changed files with 86 additions and 40 deletions
Whitespace
Show all changes Ignore whitespace when comparing lines Ignore changes in amount of whitespace Ignore changes in whitespace at EOL
Split View
Diff Options
Show Stats Download Patch File Download Diff File
  1. 3
      .github/workflows/publish.yml
  2. 52
      docs/build_docs.py
  3. 9
      docs/en/datasets/detect/open-images-v7.md
  4. 30
      docs/en/guides/object-counting.md
  5. 8
      docs/en/models/fast-sam.md
  6. 6
      docs/en/models/mobile-sam.md
  7. 8
      docs/en/models/rtdetr.md
  8. 8
      docs/en/models/sam.md
  9. 2
      ultralytics/utils/ops.py

3
.github/workflows/publish.yml
Unescape View File

@ -28,7 +28,7 @@ jobs:
- name: Set up Python environment
uses: actions/setup-python@v5
with:
python-version: '3.10'
python-version: '3.11'
cache: 'pip' # caching pip dependencies
- name: Install dependencies
run: |
@ -66,6 +66,7 @@ jobs:
env:
PERSONAL_ACCESS_TOKEN: ${{ secrets.PERSONAL_ACCESS_TOKEN }}
INDEXNOW_KEY: ${{ secrets.INDEXNOW_KEY_DOCS }}
WEGLOT_KEY: ${{ secrets.WEGLOT_KEY_DOCS }}
run: |
python docs/build_docs.py
git config --global user.name "Glenn Jocher"

52
docs/build_docs.py
Unescape View File

@ -23,14 +23,17 @@ Usage:
Note:
- This script is built to be run in an environment where Python and MkDocs are installed and properly configured.
"""
import os
import re
import shutil
import subprocess
from pathlib import Path
from tqdm import tqdm
DOCS = Path(__file__).parent.resolve()
SITE = DOCS.parent / "site"
LANGUAGES = True
def build_docs():
@ -44,9 +47,10 @@ def build_docs():
subprocess.run(f"mkdocs build -f {DOCS}/mkdocs.yml", check=True, shell=True)
# Build other localized documentations
for file in DOCS.glob("mkdocs_*.yml"):
print(f"Building MkDocs site with configuration file: {file}")
subprocess.run(f"mkdocs build -f {file}", check=True, shell=True)
if LANGUAGES:
for file in DOCS.glob("mkdocs_*.yml"):
print(f"Building MkDocs site with configuration file: {file}")
subprocess.run(f"mkdocs build -f {file}", check=True, shell=True)
print(f"Site built at {SITE}")
@ -100,19 +104,51 @@ def update_page_title(file_path: Path, new_title: str):
file.write(updated_content)
def update_html_head(key=""):
"""Update the HTML head section of each file."""
html_files = Path(SITE).rglob("*.html")
for html_file in tqdm(html_files, desc="Processing HTML files"):
with html_file.open("r", encoding="utf-8") as file:
html_content = file.read()
script = f"""
<script type="text/javascript" src="https://cdn.weglot.com/weglot.min.js"></script>
<script>
Weglot.initialize({{
api_key: '{key}'
}});
</script>
"""
if script in html_content: # script already in HTML file
return
head_end_index = html_content.lower().rfind("</head>")
if head_end_index != -1:
# Add the specified JavaScript to the HTML file just before the end of the head tag.
new_html_content = html_content[:head_end_index] + script + html_content[head_end_index:]
with html_file.open("w", encoding="utf-8") as file:
file.write(new_html_content)
def main():
# Build the docs
build_docs()
# Update titles
update_page_title(SITE / "404.html", new_title="Ultralytics Docs - Not Found")
# Update .md in href links
update_html_links()
if LANGUAGES:
update_html_links()
# Update HTML file head section
key = os.environ.get("WEGLOT_KEY")
if not LANGUAGES and key:
update_html_head(key)
# Show command to serve built website
print('Serve site at http://localhost:8000 with "python -m http.server --directory site"')
# Update titles
update_page_title(SITE / "404.html", new_title="Ultralytics Docs - Not Found")
if __name__ == "__main__":
main()

9
docs/en/datasets/detect/open-images-v7.md
Unescape View File

@ -8,6 +8,15 @@ keywords: Open Images V7, object detection, segmentation masks, visual relations
[Open Images V7](https://storage.googleapis.com/openimages/web/index.html) is a versatile and expansive dataset championed by Google. Aimed at propelling research in the realm of computer vision, it boasts a vast collection of images annotated with a plethora of data, including image-level labels, object bounding boxes, object segmentation masks, visual relationships, and localized narratives.
## Open Images V7 Pretrained Models
| Model | size<br><sup>(pixels) | mAP<sup>val<br>50-95 | Speed<br><sup>CPU ONNX<br>(ms) | Speed<br><sup>A100 TensorRT<br>(ms) | params<br><sup>(M) | FLOPs<br><sup>(B) |
|-------------------------------------------------------------------------------------------|-----------------------|----------------------|--------------------------------|-------------------------------------|--------------------|-------------------|
| [YOLOv8n](https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8n-oiv7.pt) | 640 | 18.4 | 142.4 | 1.21 | 3.5 | 10.5 |
| [YOLOv8s](https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8s-oiv7.pt) | 640 | 27.7 | 183.1 | 1.40 | 11.4 | 29.7 |
| [YOLOv8m](https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8m-oiv7.pt) | 640 | 33.6 | 408.5 | 2.26 | 26.2 | 80.6 |
| [YOLOv8l](https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8l-oiv7.pt) | 640 | 34.9 | 596.9 | 2.43 | 44.1 | 167.4 |
| [YOLOv8x](https://github.com/ultralytics/assets/releases/download/v8.1.0/yolov8x-oiv7.pt) | 640 | 36.3 | 860.6 | 3.56 | 68.7 | 260.6 |
![Open Images V7 classes visual](https://user-images.githubusercontent.com/26833433/258660358-2dc07771-ec08-4d11-b24a-f66e07550050.png)
## Key Features

30
docs/en/guides/object-counting.md
Unescape View File

@ -174,21 +174,21 @@ Object counting with [Ultralytics YOLOv8](https://github.com/ultralytics/ultraly
| Name | Type | Default | Description |
|---------------------|-------------|----------------------------|-----------------------------------------------|
| view_img | `bool` | `False` | Display frames with counts |
| view_in_counts | `bool` | `True` | Display incounts only on video frame |
| view_out_counts | `bool` | `True` | Display outcounts only on video frame |
| line_thickness | `int` | `2` | Increase bounding boxes thickness |
| reg_pts | `list` | `[(20, 400), (1260, 400)]` | Points defining the Region Area |
| classes_names | `dict` | `model.model.names` | Dictionary of Class Names |
| region_color | `RGB Color` | `(255, 0, 255)` | Color of the Object counting Region or Line |
| track_thickness | `int` | `2` | Thickness of Tracking Lines |
| draw_tracks | `bool` | `False` | Enable drawing Track lines |
| track_color | `RGB Color` | `(0, 255, 0)` | Color for each track line |
| line_dist_thresh | `int` | `15` | Euclidean Distance threshold for line counter |
| count_txt_thickness | `int` | `2` | Thickness of Object counts text |
| count_txt_color | `RGB Color` | `(0, 0, 0)` | Foreground color for Object counts text |
| count_color | `RGB Color` | `(255, 255, 255)` | Background color for Object counts text |
| region_thickness | `int` | `5` | Thickness for object counter region or line |
| `view_img` | `bool` | `False` | Display frames with counts |
| `view_in_counts` | `bool` | `True` | Display incounts only on video frame |
| `view_out_counts` | `bool` | `True` | Display outcounts only on video frame |
| `line_thickness` | `int` | `2` | Increase bounding boxes thickness |
| `reg_pts` | `list` | `[(20, 400), (1260, 400)]` | Points defining the Region Area |
| `classes_names` | `dict` | `model.model.names` | Dictionary of Class Names |
| `region_color` | `RGB Color` | `(255, 0, 255)` | Color of the Object counting Region or Line |
| `track_thickness` | `int` | `2` | Thickness of Tracking Lines |
| `draw_tracks` | `bool` | `False` | Enable drawing Track lines |
| `track_color` | `RGB Color` | `(0, 255, 0)` | Color for each track line |
| `line_dist_thresh` | `int` | `15` | Euclidean Distance threshold for line counter |
| `count_txt_thickness` | `int` | `2` | Thickness of Object counts text |
| `count_txt_color` | `RGB Color` | `(0, 0, 0)` | Foreground color for Object counts text |
| `count_color` | `RGB Color` | `(255, 255, 255)` | Background color for Object counts text |
| `region_thickness` | `int` | `5` | Thickness for object counter region or line |
### Arguments `model.track`

8
docs/en/models/fast-sam.md
Unescape View File

@ -34,10 +34,10 @@ FastSAM is designed to address the limitations of the [Segment Anything Model (S
This table presents the available models with their specific pre-trained weights, the tasks they support, and their compatibility with different operating modes like [Inference](../modes/predict.md), [Validation](../modes/val.md), [Training](../modes/train.md), and [Export](../modes/export.md), indicated by ✅ emojis for supported modes and ❌ emojis for unsupported modes.
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|------------|---------------------|----------------------------------------------|-----------|------------|----------|--------|
| FastSAM-s | `FastSAM-s.pt` | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ✅ |
| FastSAM-x | `FastSAM-x.pt` | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ✅ |
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|------------|---------------------------------------------------------------------------------------------|----------------------------------------------|-----------|------------|----------|--------|
| FastSAM-s | [FastSAM-s.pt](https://github.com/ultralytics/assets/releases/download/v8.1.0/FastSAM-s.pt) | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ✅ |
| FastSAM-x | [FastSAM-x.pt](https://github.com/ultralytics/assets/releases/download/v8.1.0/FastSAM-x.pt) | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ✅ |
## Usage Examples

6
docs/en/models/mobile-sam.md
Unescape View File

@ -20,9 +20,9 @@ MobileSAM is trained on a single GPU with a 100k dataset (1% of the original ima
This table presents the available models with their specific pre-trained weights, the tasks they support, and their compatibility with different operating modes like [Inference](../modes/predict.md), [Validation](../modes/val.md), [Training](../modes/train.md), and [Export](../modes/export.md), indicated by ✅ emojis for supported modes and ❌ emojis for unsupported modes.
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|------------|---------------------|----------------------------------------------|-----------|------------|----------|--------|
| MobileSAM | `mobile_sam.pt` | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ❌ |
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|------------|-----------------------------------------------------------------------------------------------|----------------------------------------------|-----------|------------|----------|--------|
| MobileSAM | [mobile_sam.pt](https://github.com/ultralytics/assets/releases/download/v8.1.0/mobile_sam.pt) | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ❌ |
## Adapting from SAM to MobileSAM

8
docs/en/models/rtdetr.md
Unescape View File

@ -63,10 +63,10 @@ This example provides simple RT-DETRR training and inference examples. For full
This table presents the model types, the specific pre-trained weights, the tasks supported by each model, and the various modes ([Train](../modes/train.md) , [Val](../modes/val.md), [Predict](../modes/predict.md), [Export](../modes/export.md)) that are supported, indicated by ✅ emojis.
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|---------------------|---------------------|----------------------------------------|-----------|------------|----------|--------|
| RT-DETR Large | `rtdetr-l.pt` | [Object Detection](../tasks/detect.md) | ✅ | ✅ | ✅ | ✅ |
| RT-DETR Extra-Large | `rtdetr-x.pt` | [Object Detection](../tasks/detect.md) | ✅ | ✅ | ✅ | ✅ |
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|---------------------|-------------------------------------------------------------------------------------------|----------------------------------------|-----------|------------|----------|--------|
| RT-DETR Large | [rtdetr-l.pt](https://github.com/ultralytics/assets/releases/download/v8.1.0/rtdetr-l.pt) | [Object Detection](../tasks/detect.md) | ✅ | ✅ | ✅ | ✅ |
| RT-DETR Extra-Large | [rtdetr-x.pt](https://github.com/ultralytics/assets/releases/download/v8.1.0/rtdetr-x.pt) | [Object Detection](../tasks/detect.md) | ✅ | ✅ | ✅ | ✅ |
## Citations and Acknowledgements

8
docs/en/models/sam.md
Unescape View File

@ -29,10 +29,10 @@ For an in-depth look at the Segment Anything Model and the SA-1B dataset, please
This table presents the available models with their specific pre-trained weights, the tasks they support, and their compatibility with different operating modes like [Inference](../modes/predict.md), [Validation](../modes/val.md), [Training](../modes/train.md), and [Export](../modes/export.md), indicated by ✅ emojis for supported modes and ❌ emojis for unsupported modes.
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|------------|---------------------|----------------------------------------------|-----------|------------|----------|--------|
| SAM base | `sam_b.pt` | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ❌ |
| SAM large | `sam_l.pt` | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ❌ |
| Model Type | Pre-trained Weights | Tasks Supported | Inference | Validation | Training | Export |
|------------|-------------------------------------------------------------------------------------|----------------------------------------------|-----------|------------|----------|--------|
| SAM base | [sam_b.pt](https://github.com/ultralytics/assets/releases/download/v8.1.0/sam_b.pt) | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ❌ |
| SAM large | [sam_l.pt](https://github.com/ultralytics/assets/releases/download/v8.1.0/sam_l.pt) | [Instance Segmentation](../tasks/segment.md) | ✅ | ❌ | ❌ | ❌ |
## How to Use SAM: Versatility and Power in Image Segmentation

2
ultralytics/utils/ops.py
Unescape View File

@ -547,7 +547,7 @@ def xywhr2xyxyxyxy(rboxes):
be in degrees from 0 to 90.
Args:
center (numpy.ndarray | torch.Tensor): Input data in [cx, cy, w, h, rotation] format of shape (n, 5) or (b, n, 5).
rboxes (numpy.ndarray | torch.Tensor): Input data in [cx, cy, w, h, rotation] format of shape (n, 5) or (b, n, 5).
Returns:
(numpy.ndarray | torch.Tensor): Converted corner points of shape (n, 4, 2) or (b, n, 4, 2).

Write Preview
Loading…
Cancel
Save