Comments (2)
Elegant? No. 😆
My initial thinking was similar to your description. I imagined a few subclasses of Keras’s model class, e.g. an RPN model, an RCNN model, and a MaskRCNN model.
However, I think there’d be some benefit of something more modular. @mcquin has been thinking about this problem. I’d love to hear her thoughts.
I’ve also considered reaching out to @KaimingHe, @rbgirshick, @pdollar, etc. and asking for feedback. I’d especially like to hear feedback from @rbgirshick about his current thinking around RCNN implementation after writing and maintaining py-faster-rcnn for the past year or two.
@JihongJu Are you planning on attending CVPR? A few of us will be attending (@jhung0 and I are attending), so maybe we can talk about future plans (I assume some of the aforementioned RCNN authors are attending too). SciPy is another option (@mcquin is attending). Alternatively, we could schedule a Skype call for anybody that’s interested.
When we (@jhung0, @mcquin, @AnneCarpenter, and I) first started discussing this , I wrote the following simple description in my notebook:
Keras-RCNN is a framework for solving image segmentation and object detection problems.
I still think this captures what I hope this becomes (rather than the application approach provided by py-faster-rcnn or yolo). I imagine us trying to stay state-of-the-art (inside the scope of RCNN) but enabling users to mix-and-match components (like a Mask-RCNN branch).
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@0x00b1 Unfortunately, I am not attending CVPR this year. A Skype call would work the best for me because I am now located in Europe.
I still think this captures what I hope this becomes (rather than the application approach provided by py-faster-rcnn or yolo). I imagine us trying to stay state-of-the-art (inside the scope of RCNN) but enabling users to mix-and-match components (like a Mask-RCNN branch).
I totally agree with the components mix-and-match pattern. That is also what I have in mind.
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Related Issues (20)
- masks for dsb18 are off
- Generator limits image pixel range 0 to 1
- nans during RPN training HOT 4
- Remove boxes at the edge
- Model is not saved using model.save("model.h5") HOT 3
- KeyError when trying out the Example HOT 1
- AttributeError: module 'keras.engine' has no attribute 'topology' HOT 3
- Path Aggregation Network for Instance Segmentation
- Error while calculating val_loss using validation_data HOT 1
- Misspelling in README.rst
- README, the parameter position is wrong
- Error reading B&W object
- Unable to load the datasets in keras_rcnn
- Generating json of images with no object of concern.
- How to calculate the accuracy of the model that is generated?
- No module named 'keras_resnet' HOT 1
- AttributeError: module 'keras_resnet.models' has no attribute 'FPN2D50' HOT 1
- Tensorflow 2.x upgrade
- AttributeError: 'Node' object has no attribute 'output_masks' HOT 6
- share pretrained weights
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