Skip to content

fix: Modify some expressions in the thresholding tutorial #11

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Merged
merged 2 commits into from
Apr 12, 2020
Merged
Changes from all commits
Commits
File filter

Filter by extension

Filter by extension

Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
4 changes: 2 additions & 2 deletions 06. 阈值分割/README.md
Original file line number Diff line number Diff line change
Expand Up @@ -35,7 +35,7 @@ cv2.waitKey(0)

- 参数1:要处理的原图,**一般是灰度图**
- 参数2:设定的阈值
- 参数3:最大阈值,一般为255
- 参数3:对于`THRESH_BINARY`、`THRESH_BINARY_INV`阈值方法所选用的最大阈值,一般为255
- 参数4:阈值的方式,主要有5种,详情:[ThresholdTypes](https://docs.opencv.org/4.0.0/d7/d1b/group__imgproc__misc.html#gaa9e58d2860d4afa658ef70a9b1115576)

下面结合代码理解下这5种阈值方式:
Expand Down Expand Up @@ -102,7 +102,7 @@ plt.show()
- 参数3:小区域阈值的计算方式
- `ADAPTIVE_THRESH_MEAN_C`:小区域内取均值
- `ADAPTIVE_THRESH_GAUSSIAN_C`:小区域内加权求和,权重是个高斯核
- 参数4:阈值方式(跟前面讲的那5种相同)
- 参数4:阈值方法,只能使用`THRESH_BINARY`、`THRESH_BINARY_INV`,具体见前面所讲的阈值方法
- 参数5:小区域的面积,如11就是11*11的小块
- 参数6:最终阈值等于小区域计算出的阈值再减去此值

Expand Down