potok/opencv
1
0
Fork 0
mirror of https://github.com/opencv/opencv.git synced 2026-07-30 07:43:03 +04:00
Code Packages Releases Wiki Activity

Merge pull request #27338 from omahs:patch-1

Browse Source 
Fix typos #27338

### Pull Request Readiness Checklist

See details at https://github.com/opencv/opencv/wiki/How_to_contribute#making-a-good-pull-request

- [x] I agree to contribute to the project under Apache 2 License.
- [x] To the best of my knowledge, the proposed patch is not based on a code under GPL or another license that is incompatible with OpenCV
- [x] The PR is proposed to the proper branch
- [ ] There is a reference to the original bug report and related work
- [ ] There is accuracy test, performance test and test data in opencv_extra repository, if applicable
      Patch to opencv_extra has the same branch name.
- [ ] The feature is well documented and sample code can be built with the project CMake
This commit is contained in:
omahs
2025-05-21 11:13:50 +02:00
committed by GitHub
parent dc610867e1
commit 0bc95d9256
14 changed files with 19 additions and 19 deletions
Download Patch File Download Diff File Expand all files Collapse all files
doc/tutorials/dnn/dnn_yolo/dnn_yolo.markdown
+1 -1
View File
@@ -41,7 +41,7 @@ Assuming that we have successfully trained YOLOX model, the subsequent step invo
running this model with OpenCV. There are several critical considerations to address before
proceeding with this process. Let's delve into these aspects.
### YOLO's Pre-proccessing & Output
### YOLO's Pre-processing & Output
Understanding the nature of inputs and outputs associated with YOLO family detectors is pivotal.
These detectors, akin to most Deep Neural Networks (DNN), typically exhibit variation in input