HongChuang/ultralytics-ascend
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity Actions 3

Mkdocs annotations fixes (#7600)

Browse source 
Signed-off-by: Glenn Jocher <glenn.jocher@ultralytics.com>
This commit is contained in:
Glenn Jocher 2024-01-15 23:37:37 +01:00 • committed by GitHub
parent 22651d01cf
commit b1282544d2
No known key found for this signature in database
GPG key ID: 4AEE18F83AFDEB23
24 changed files with 137 additions and 63 deletions
Download patch file Download diff file Expand all files Collapse all files

1
docs/en/modes/benchmark.md
View file

@ -62,6 +62,7 @@ Run YOLOv8n benchmarks on all supported export formats including ONNX, TensorRT
# Benchmark on GPU
benchmark(model='yolov8n.pt', data='coco8.yaml', imgsz=640, half=False, device=0)
```
=== "CLI"
```bash

1
docs/en/modes/export.md
View file

@ -62,6 +62,7 @@ Export a YOLOv8n model to a different format like ONNX or TensorRT. See Argument
# Export the model
model.export(format='onnx')
```
=== "CLI"
```bash

59
docs/en/modes/predict.md
View file

@ -53,6 +53,7 @@ Ultralytics YOLO models return either a Python list of `Results` objects, or a m
!!! Example "Predict"
=== "Return a list with `stream=False`"
```python
from ultralytics import YOLO
@ -71,6 +72,7 @@ Ultralytics YOLO models return either a Python list of `Results` objects, or a m
```
=== "Return a generator with `stream=True`"
```python
from ultralytics import YOLO
@ -118,6 +120,7 @@ Below are code examples for using each source type:
!!! Example "Prediction sources"
=== "image"
Run inference on an image file.
```python
from ultralytics import YOLO
@ -133,6 +136,7 @@ Below are code examples for using each source type:
```
=== "screenshot"
Run inference on the current screen content as a screenshot.
```python
from ultralytics import YOLO
@ -148,6 +152,7 @@ Below are code examples for using each source type:
```
=== "URL"
Run inference on an image or video hosted remotely via URL.
```python
from ultralytics import YOLO
@ -163,6 +168,7 @@ Below are code examples for using each source type:
```
=== "PIL"
Run inference on an image opened with Python Imaging Library (PIL).
```python
from PIL import Image
@ -179,6 +185,7 @@ Below are code examples for using each source type:
```
=== "OpenCV"
Run inference on an image read with OpenCV.
```python
import cv2
@ -195,6 +202,7 @@ Below are code examples for using each source type:
```
=== "numpy"
Run inference on an image represented as a numpy array.
```python
import numpy as np
@ -211,6 +219,7 @@ Below are code examples for using each source type:
```
=== "torch"
Run inference on an image represented as a PyTorch tensor.
```python
import torch
@ -227,6 +236,7 @@ Below are code examples for using each source type:
```
=== "CSV"
Run inference on a collection of images, URLs, videos and directories listed in a CSV file.
```python
import torch
@ -243,6 +253,7 @@ Below are code examples for using each source type:
```
=== "video"
Run inference on a video file. By using `stream=True`, you can create a generator of Results objects to reduce memory usage.
```python
from ultralytics import YOLO
@ -258,6 +269,7 @@ Below are code examples for using each source type:
```
=== "directory"
Run inference on all images and videos in a directory. To also capture images and videos in subdirectories use a glob pattern, i.e. `path/to/dir/**/*`.
```python
from ultralytics import YOLO
@ -273,6 +285,7 @@ Below are code examples for using each source type:
```
=== "glob"
Run inference on all images and videos that match a glob expression with `*` characters.
```python
from ultralytics import YOLO
@ -291,6 +304,7 @@ Below are code examples for using each source type:
```
=== "YouTube"
Run inference on a YouTube video. By using `stream=True`, you can create a generator of Results objects to reduce memory usage for long videos.
```python
from ultralytics import YOLO
@ -306,6 +320,7 @@ Below are code examples for using each source type:
```
=== "Streams"
Run inference on remote streaming sources using RTSP, RTMP, TCP and IP address protocols. If multiple streams are provided in a `*.streams` text file then batched inference will run, i.e. 8 streams will run at batch-size 8, otherwise single streams will run at batch-size 1.
```python
from ultralytics import YOLO
@ -384,16 +399,16 @@ The below table contains valid Ultralytics image formats.
| Image Suffixes | Example Predict Command | Reference |
|----------------|----------------------------------|-------------------------------------------------------------------------------|
| .bmp | `yolo predict source=image.bmp` | [Microsoft BMP File Format](https://en.wikipedia.org/wiki/BMP_file_format) |
| .dng | `yolo predict source=image.dng` | [Adobe DNG](https://www.adobe.com/products/photoshop/extend.displayTab2.html) |
| .jpeg | `yolo predict source=image.jpeg` | [JPEG](https://en.wikipedia.org/wiki/JPEG) |
| .jpg | `yolo predict source=image.jpg` | [JPEG](https://en.wikipedia.org/wiki/JPEG) |
| .mpo | `yolo predict source=image.mpo` | [Multi Picture Object](https://fileinfo.com/extension/mpo) |
| .png | `yolo predict source=image.png` | [Portable Network Graphics](https://en.wikipedia.org/wiki/PNG) |
| .tif | `yolo predict source=image.tif` | [Tag Image File Format](https://en.wikipedia.org/wiki/TIFF) |
| .tiff | `yolo predict source=image.tiff` | [Tag Image File Format](https://en.wikipedia.org/wiki/TIFF) |
| .webp | `yolo predict source=image.webp` | [WebP](https://en.wikipedia.org/wiki/WebP) |
| .pfm | `yolo predict source=image.pfm` | [Portable FloatMap](https://en.wikipedia.org/wiki/Netpbm#File_formats) |
| `.bmp` | `yolo predict source=image.bmp` | [Microsoft BMP File Format](https://en.wikipedia.org/wiki/BMP_file_format) |
| `.dng` | `yolo predict source=image.dng` | [Adobe DNG](https://www.adobe.com/products/photoshop/extend.displayTab2.html) |
| `.jpeg` | `yolo predict source=image.jpeg` | [JPEG](https://en.wikipedia.org/wiki/JPEG) |
| `.jpg` | `yolo predict source=image.jpg` | [JPEG](https://en.wikipedia.org/wiki/JPEG) |
| `.mpo` | `yolo predict source=image.mpo` | [Multi Picture Object](https://fileinfo.com/extension/mpo) |
| `.png` | `yolo predict source=image.png` | [Portable Network Graphics](https://en.wikipedia.org/wiki/PNG) |
| `.tif` | `yolo predict source=image.tif` | [Tag Image File Format](https://en.wikipedia.org/wiki/TIFF) |
| `.tiff` | `yolo predict source=image.tiff` | [Tag Image File Format](https://en.wikipedia.org/wiki/TIFF) |
| `.webp` | `yolo predict source=image.webp` | [WebP](https://en.wikipedia.org/wiki/WebP) |
| `.pfm` | `yolo predict source=image.pfm` | [Portable FloatMap](https://en.wikipedia.org/wiki/Netpbm#File_formats) |
### Videos
@ -401,18 +416,18 @@ The below table contains valid Ultralytics video formats.
| Video Suffixes | Example Predict Command | Reference |
|----------------|----------------------------------|----------------------------------------------------------------------------------|
| .asf | `yolo predict source=video.asf` | [Advanced Systems Format](https://en.wikipedia.org/wiki/Advanced_Systems_Format) |
| .avi | `yolo predict source=video.avi` | [Audio Video Interleave](https://en.wikipedia.org/wiki/Audio_Video_Interleave) |
| .gif | `yolo predict source=video.gif` | [Graphics Interchange Format](https://en.wikipedia.org/wiki/GIF) |
| .m4v | `yolo predict source=video.m4v` | [MPEG-4 Part 14](https://en.wikipedia.org/wiki/M4V) |
| .mkv | `yolo predict source=video.mkv` | [Matroska](https://en.wikipedia.org/wiki/Matroska) |
| .mov | `yolo predict source=video.mov` | [QuickTime File Format](https://en.wikipedia.org/wiki/QuickTime_File_Format) |
| .mp4 | `yolo predict source=video.mp4` | [MPEG-4 Part 14 - Wikipedia](https://en.wikipedia.org/wiki/MPEG-4_Part_14) |
| .mpeg | `yolo predict source=video.mpeg` | [MPEG-1 Part 2](https://en.wikipedia.org/wiki/MPEG-1) |
| .mpg | `yolo predict source=video.mpg` | [MPEG-1 Part 2](https://en.wikipedia.org/wiki/MPEG-1) |
| .ts | `yolo predict source=video.ts` | [MPEG Transport Stream](https://en.wikipedia.org/wiki/MPEG_transport_stream) |
| .wmv | `yolo predict source=video.wmv` | [Windows Media Video](https://en.wikipedia.org/wiki/Windows_Media_Video) |
| .webm | `yolo predict source=video.webm` | [WebM Project](https://en.wikipedia.org/wiki/WebM) |
| `.asf` | `yolo predict source=video.asf` | [Advanced Systems Format](https://en.wikipedia.org/wiki/Advanced_Systems_Format) |
| `.avi` | `yolo predict source=video.avi` | [Audio Video Interleave](https://en.wikipedia.org/wiki/Audio_Video_Interleave) |
| `.gif` | `yolo predict source=video.gif` | [Graphics Interchange Format](https://en.wikipedia.org/wiki/GIF) |
| `.m4v` | `yolo predict source=video.m4v` | [MPEG-4 Part 14](https://en.wikipedia.org/wiki/M4V) |
| `.mkv` | `yolo predict source=video.mkv` | [Matroska](https://en.wikipedia.org/wiki/Matroska) |
| `.mov` | `yolo predict source=video.mov` | [QuickTime File Format](https://en.wikipedia.org/wiki/QuickTime_File_Format) |
| `.mp4` | `yolo predict source=video.mp4` | [MPEG-4 Part 14 - Wikipedia](https://en.wikipedia.org/wiki/MPEG-4_Part_14) |
| `.mpeg` | `yolo predict source=video.mpeg` | [MPEG-1 Part 2](https://en.wikipedia.org/wiki/MPEG-1) |
| `.mpg` | `yolo predict source=video.mpg` | [MPEG-1 Part 2](https://en.wikipedia.org/wiki/MPEG-1) |
| `.ts` | `yolo predict source=video.ts` | [MPEG Transport Stream](https://en.wikipedia.org/wiki/MPEG_transport_stream) |
| `.wmv` | `yolo predict source=video.wmv` | [Windows Media Video](https://en.wikipedia.org/wiki/Windows_Media_Video) |
| `.webm` | `yolo predict source=video.webm` | [WebM Project](https://en.wikipedia.org/wiki/WebM) |
## Working with Results

4
docs/en/modes/train.md
View file

@ -241,6 +241,7 @@ To use Comet:
!!! Example
=== "Python"
```python
# pip install comet_ml
import comet_ml
@ -259,6 +260,7 @@ To use ClearML:
!!! Example
=== "Python"
```python
# pip install clearml
import clearml
@ -277,6 +279,7 @@ To use TensorBoard in [Google Colab](https://colab.research.google.com/github/ul
!!! Example
=== "CLI"
```bash
load_ext tensorboard
tensorboard --logdir ultralytics/runs # replace with 'runs' directory
@ -287,6 +290,7 @@ To use TensorBoard locally run the below command and view results at http://loca
!!! Example
=== "CLI"
```bash
tensorboard --logdir ultralytics/runs # replace with 'runs' directory
```

1
docs/en/modes/val.md
View file

@ -67,6 +67,7 @@ Validate trained YOLOv8n model accuracy on the COCO128 dataset. No argument need
metrics.box.map75 # map75
metrics.box.maps # a list contains map50-95 of each category
```
=== "CLI"
```bash