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Result of My Cascade Training is Bad

asked 2020-11-20 16:56:26 -0600

BurakM gravatar image

Hello everyone,

I want make a fish detection using haar cascade. I have 183 positive, 270 negative images. Training is completed in a short time. But results are very bad, terrible. I attached positive,negative samples and result.

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answered 2020-11-21 02:13:53 -0600

berak gravatar image

yea, that's expected. cascades are for rigid things with reliable texture and pose.

that's not, what you have.

you probably tried to train it on "aquarium fish", but that's a far too broad category, and any variation in pose or texture will degrade the detection

I have 183 positive, 270 negative images.

even if it were the appropriate method, you would need like 50x the data

to train something successful,

  • you need a lot more data
  • a different mechanism (e.g. retrain a detection cnn, like yolo or ssd)
  • more refined categories / object classes
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Thank's your answer. My lectrurer want cascade so i can't use yolo tenserflow etc. Should I have 5 thousand positive 10 thousand negatives? I have a hard time finding the negatives. There is not much underwater photograph without fish. Do you know where I can find more data?

BurakM gravatar imageBurakM ( 2020-12-02 13:27:31 -0600 )edit

My lectrurer want cascade

that person is an idiot. change school/uni, seriously.

for cascades, you need a lot of positives (cropped), but if your negatives are large enough, not so many (it will take "windows" from that). you can also "black out" the fish from a positive image, and use that as a negative

if you really want(or must) to use cascades, make sure:

  • to restrict it to a single kind of fish
  • use a single pose only (like horizontal, head pointing to the left. if it's otherwise, mirror the image)
berak gravatar imageberak ( 2020-12-02 13:37:48 -0600 )edit

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Asked: 2020-11-20 16:56:26 -0600

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Last updated: Nov 21 '20