Which detection model will give more accuracy for arial view image detection!

[Morganh]

Hi samjith888,
As mentioned previously, you need to trigger experiments.To improve accuracy on small objects, the most common trick is to use a smaller set of anchors. The anchor sizes should have a size that is similar to the small objects’ size. Anchor ratios can be kept unchanged.
You can also train only two classes firstly instead of 5 classes. Trigger less classes in order to narrow down.
Mssing_P 25x23
Extra_P 26X13

Note that for above size, since you change from 40962160 to 1024544, you need to make anchor sizes cover
25/4 * 23/4
26/4 * 13/4

[samjith888]

@Morganh

Hi samjith888,
As mentioned previously, you need to trigger experiments.To improve accuracy on small objects, the most common trick is to use a smaller set of anchors. The anchor sizes should have a size that is similar to the small objects’ size. Anchor ratios can be kept unchanged.
You can also train only two classes firstly instead of 5 classes. Trigger less classes in order to narrow down.
Mssing_P 25x23
Extra_P 26X13

Note that for above size, since you change from 40962160 to 1024544, you need to make anchor sizes cover
25/4 * 23/4
26/4 * 13/4

How to change the anchor sizes to cover the above anchor sizes?

anchor_box_config {
scale: 8.0
scale: 16.0
scale: 32.0
ratio: 1.0
ratio: 0.5
ratio: 2.0
}

[Morganh]

Refer to the way in https://devtalk.nvidia.com/default/topic/1069737/transfer-learning-toolkit/which-detection-model-will-give-more-accuracy-for-arial-view-image-detection-/post/5420836/#5420836,
for the two small objects,
Mssing_P 25x23
Extra_P 26X13

since you change from 4096x2160 to 1024x544, so it becomes
6.25x5.75
6.5x3.25

You can try

anchor_box_config {
scale: 4.0
scale: 4.6
scale: 5.0
ratio: 1.0
ratio: 0.5
ratio: 2.0
}

It can cover anchor sizes like
4x4,
2.828x5.656
5.656x2.828
4.6x4.6
3.25x6.5
6.5x3.25
5x5
3.535x7.07
7.07x3.535

[samjith888]

can i use different resolution images for training ?

[Morganh]

Sure, you can set your original resolution to others.
Then calculate the new pixels range of the small objects. And set a better anchor_box_config.

[samjith888]

Hi Morganh,

I meant that i have a data set which consist of images with different resolutions ( eg:41202240, 800450, 1080120 ,300 250 etc). So can i use this dataset for training? Or TLT didn’t only unique sized images ?

[Morganh]

For detectnet_2 and SSD network, all of the images must be resized offline to the final training size.
For faster-rcnn, you don’t need to resize the image.

See tlt user guide’s chapter 2 for more details.