Image segmentation workflow #830
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Haha, Greg, this is so cool, seems you've been busy. I don't see any significant conflicts with #777 if I skim through the Files Changed. I will test this weekend. I'm unsure if your 3 bulletpoints cover the +1600 locs though, anything else to keep an eye out for? |
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Hello, I'm getting an error "Check failed: registry.count(type) == 1 (0 vs. 1) Unknown layer type: L1Loss" when I attempt to create a model using the tutorial. Is there an alternative? |
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Hello, to use the Caffe model you need nv-caffe 0.15. Or you can use |
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EuclideanLoss with learning rate 1e-7 worked. Thanks! |
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Hi @gheinrich I would like to know if you might have worked on more complex models for image segmentation to test this branch. I would be interested to test on some of my own dataset. |
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Hello @hariprasadravi I haven't yet found the time to try more complex problems. I highly recommend this paper though: Fully Convolutional Networks for Semantic Segmentation |
| tooltip="Indicate a folder full of images. There must be one " | ||
| "image per image in the source image folder. Image " | ||
| "names do not matter but the images should match " | ||
| "those of the source folder, when sorted alphanumerically." |
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This seems a bit loose to me. Why not match the KITTI format and require matching filenames (without extensions)?
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I agree... I made it like this initially because in the first dataset I used all images were one off e.g. img1.jpg in target folder corresponded to img0.jpg in source folder. I can change this.
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Made it through the tutorial - this is super cool! |
To be used with networks where the input and the output are images
Labels were restricted to scalars (classification) or vectors (regression). This change extends supported label types to anything that fits in an LMDB. Small refactoring of datum decoding.
Caffe and Torch pre-processors are updated to handle the case where the input image dimensions do not match those of the training set.
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Image segmentation workflow
I am planning to break this down into smaller PRs but I am interested in getting early feedback.
This PR builds upon #806 and adds:
Datumobject)@pansk @TimZaman : would you like to have a look?
I understand some of these changes might conflict with #777. I am willing to wait for #777 to be merged first then I will rebase.