增加翻译内容,更新 GIF 视频.

Signed-off-by: rick.chan <chenyang@autoai.com>
This commit is contained in:
rick.chan 2020-11-24 11:55:09 +08:00
parent facaf8f4cf
commit 17be8bcb29
2 changed files with 6 additions and 4 deletions

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@ -115,9 +115,9 @@ Haar 级联分类器最著名的应用是检测图像中的人脸或身体,但
“If a picture is worth a thousand words this would be a million words. This is where it all comes together. The Ahh-hah moment.” “If a picture is worth a thousand words this would be a million words. This is where it all comes together. The Ahh-hah moment.”
“This simple video helped crystalize for me how this algorithm works. Here are some observations: “This simple video helped crystalize for me how this algorithm works. Here are some observations:
* Notice how the algorithm moves the window systematically over the image, applying the Haar features as it is trying to detect the face. This is depicted by the green rectangles. * Notice how the algorithm moves the window systematically over the image, applying the Haar features as it is trying to detect the face. This is depicted by the green rectangles.
* Notice underneath the red boundary square, we see the classifier executing stages quickly discarding window frames that are clearly not a match (stages 1-25) * Notice underneath the red boundary square, we see the classifier executing stages quickly discarding window frames that are clearly not a match (stages 1-25)
* To the right of the stage we see the how well it performed in identifying the face. * To the right of the stage we see the how well it performed in identifying the face.
* Notice as it gets closer and closer to identifying the face, the number of stages increases into the 20s. (around the 1 minute mark). This demonstrates the cascading effect where the early stages are discarding the input as it has identified them as irrelevant. As it gets closer to finding a face it pays closer attention.” * Notice as it gets closer and closer to identifying the face, the number of stages increases into the 20s. (around the 1 minute mark). This demonstrates the cascading effect where the early stages are discarding the input as it has identified them as irrelevant. As it gets closer to finding a face it pays closer attention.”
@ -128,11 +128,13 @@ Haar 级联分类器最著名的应用是检测图像中的人脸或身体,但
“Let me know if you have any questions or have any comments below.” “Let me know if you have any questions or have any comments below.”
“I want to make sure I got this post right. It will be critical that you understand this before we go into the next section where we will implement a full Custom Object Haar Cascade detector.” “I want to make sure I got this post right. It will be critical that you understand this before we go into the next section where we will implement a full Custom Object Haar Cascade detector.”
## Next Steps ## Next Steps
“I don't know about you, but I find the best way to understand something is by doing it. Conceptually we now have an idea for how the machine learning Haar Cascade object detection works. Now lets build a real world custom Object Detector, train it, and see it in action. I have a really cool example for us! Click on the button below.” “I don't know about you, but I find the best way to understand something is by doing it. Conceptually we now have an idea for how the machine learning Haar Cascade object detection works. Now lets build a real world custom Object Detector, train it, and see it in action. I have a really cool example for us! Click on the button below.”
按钮的连接错了,所以我实在不知道作者所说的 cool example 是哪一个,不过作者网站确实有一些很酷的例子,感兴趣的朋友可以点击连接进入[作者网站](http://www.willberger.org/category/ai/),也可以自行练习一些例子,毕竟理解事物的最好方法就是实践。
## References ## References

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