How to run the semantic segmentation on my own images? about ademxapp HOT 11 CLOSED

ok so I managed to run it on my own images but I have some large staircase type of effects, not sure why? is it due to the pre-trained models which has run on low res images and consequently if I run on high resolution images some interpolation is done to upscale the segmentation? Do I need to tweak the code to get better results or this is a model limitation ? (the below is a person standing and his legs do not have such a staircase profil)

from ademxapp.

Hi, Tetsujinfr. Thanks for your share. May I ask how I can get a segmented image on my own image like the picture you posted?

from ademxapp.

@Tetsujinfr

from ademxapp.

Hi sure. Let me post the bits and pieces I did modify later today (can not right now). Warning: this is a quick and dirty hack of the code bit it works to test on new data. Will post the code and and an example of th command line.

from ademxapp.

Thanks a lot.

from ademxapp.

ok, I attach the modified file data.py and the modified voc.py (voctets.py here). Basically I de-acivated the part which is doing the validation scoring in the voc file. So put your images into a folder, say ademxapp/myInputImages, then go into this folcer and do a "ls *.jpg

myInputImages.lst" to generate the file containing the images inventory to process. Then call voctets.py as sudo with --data-root /myInputImages and it should work.
An example:
python issegm/tetsvoc.py --data-root data/myPNGImages --output outputTets --phase val --weights models/voc_rna-a1_cls21_s8_ep-0001.params --split val --test-scales 720 --test-flipping --gpus 0

(I did attach the py files as .txt so that I can attach them but please remove the .txt extension)
Hope it helps.

I did run the model over a few video, have a look at my youtube channel, I will post some results soon:
https://www.youtube.com/channel/UCZUuytmk4SbmKVDgqhq24Kw
Some hint:

Tets

data.py.txt
tetsvoc.py.txt

from ademxapp.

Thanks for your share. Great help.

from ademxapp.

I will close this issue in the next couple days if no more question.

from ademxapp.

Hi Testsujinfr,

thanks for your instructions. Did you finally find out why there is this "staircase effect" ?

Thank you

from ademxapp.

Not fully although I suspect it is due to the resolution of the training dataset of the model, which I think take 224x224 pixel input images. So ultimately for large hi res image, the model is going to interpolate somehow, and it seems it is doing that is a squarry way as a default. I did not dig it further. I liked this project, one of the best results I have seen on segmentation so far, but I am not an expert in the field.

from ademxapp.

Although the issue has been closed, if you want to train/test the network with a personal dataset, please edit the "train.lst/val.lst" in the "issegm/data/voc/" and replace the images in the "data/VOCdevkit/VOC2012/JPEGImages" and "data/VOCdevkit/VOC2012/SegmentationClass" with yours.
.

from ademxapp.