Comments (7)
they didnt give out the rotated model....
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@9rck No need to retrain a rotated model.
I managed to get rotated face detection working with the provided model facefinder
.
Nothing special has been done, just remember the angle
argument should be in range 0.0-1.0.
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@liberize can you pls tell me how to use this argument?
I tried to add -a 0.0-1.0 and it's not work.
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@9crk
I didn't test the sample program, instead, I used the code directly in my own project.
Here is some code snippets, hope it might help:
https://gist.github.com/liberize/6672f53abfa871ba520c28d37365a939
PS: I modified the cluster_detections
interface and added some code to get in-plane rotation angle.
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I have to say, the result is not good.
Some problems I have discovered:
- the angle calculated with maximum total quality as I did in the code above is wrong sometimes.
- the face rect is not accurate, sometimes too small only part of face, sometimes false positive, ...
I also tried to train a new model with part of ibug 300w dataset, still not good.
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额。。都是**人啊。。。
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@liberize could you like to show us your cluster_detections code?
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Related Issues (20)
- The details in Training HOT 5
- tree tdepth HOT 2
- the method is fast!
- Rectangular detection HOT 1
- train data problem HOT 1
- Problem in training my
- Problem in training my own detectors HOT 2
- it's not faster than OpenCV 3.1
- Background dataset HOT 2
- Advice on training custom detectors? HOT 4
- model can't converge HOT 16
- Problems about accelerating the speed of inference stage HOT 2
- Scanner logic should be from largest to smallest
- Could I ask what does s = 2.0*1.5*eyedist means in caltechfaces.py?
- what should I set ldim to? HOT 4
- Understanding tsr tsc parameters HOT 1
- Can i improve the code for eye detction HOT 1
- understanding the lut parameter HOT 1
- no documentation for learning custom detectors
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