xdobro23/YOLOv8-16bit
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Update license and tasks docs (#2941)

Browse Source
This commit is contained in:
Glenn Jocher
2023-06-01 00:42:55 +02:00
committed by GitHub
parent c050b2d1a8
commit 96fb5ee78e
9 changed files with 25 additions and 8 deletions
Download Patch File Download Diff File Expand all files Collapse all files

3
docs/tasks/classify.md
View File

@ -6,7 +6,8 @@ description: Check YOLO class label with only one class for the whole image, usi
Image classification is the simplest of the three tasks and involves classifying an entire image into one of a set of
predefined classes.
<img width="1024" src="https://user-images.githubusercontent.com/26833433/212094133-6bb8c21c-3d47-41df-a512-81c5931054ae.png">
<br>
<img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/tasks/im/banner-tasks.png">
The output of an image classifier is a single class label and a confidence score. Image
classification is useful when you need to know only what class an image belongs to and don't need to know where objects

3
docs/tasks/detect.md
View File

@ -5,7 +5,8 @@ description: Learn how to use YOLOv8, an object detection model pre-trained with
Object detection is a task that involves identifying the location and class of objects in an image or video stream.
<img width="1024" src="https://user-images.githubusercontent.com/26833433/212094133-6bb8c21c-3d47-41df-a512-81c5931054ae.png">
<br>
<img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/tasks/im/banner-tasks.png">
The output of an object detector is a set of bounding boxes that enclose the objects in the image, along with class labels and confidence scores for each box. Object detection is a good choice when you need to identify objects of interest in a scene, but don't need to know exactly where the object is or its exact shape.

3
docs/tasks/index.md
View File

@ -9,7 +9,8 @@ YOLOv8 is an AI framework that supports multiple computer vision **tasks**. The
perform [detection](detect.md), [segmentation](segment.md), [classification](classify.md),
and [pose](pose.md) estimation. Each of these tasks has a different objective and use case.
<img width="1024" src="https://user-images.githubusercontent.com/26833433/212094133-6bb8c21c-3d47-41df-a512-81c5931054ae.png">
<br>
<img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/tasks/im/banner-tasks.png">
## [Detection](detect.md)

3
docs/tasks/segment.md
View File

@ -6,7 +6,8 @@ description: Learn what Instance segmentation is. Get pretrained YOLOv8 segment
Instance segmentation goes a step further than object detection and involves identifying individual objects in an image
and segmenting them from the rest of the image.
<img width="1024" src="https://user-images.githubusercontent.com/26833433/212094133-6bb8c21c-3d47-41df-a512-81c5931054ae.png">
<br>
<img width="1024" src="https://raw.githubusercontent.com/ultralytics/assets/tasks/im/banner-tasks.png">
The output of an instance segmentation model is a set of masks or
contours that outline each object in the image, along with class labels and confidence scores for each object. Instance