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If you are trying to do something completely new, you may wish to implement a model entirely from scratch within detectron2. However, in many situations you may be interested in modifying or extending some components of an existing model. Therefore, we also provide a registration mechanism that lets you override the behavior of certain internal components of standard models.
For example, to add a new backbone, import this code in your code:
from detectron2.modeling import BACKBONE_REGISTRY, Backbone, ShapeSpec
@BACKBONE_REGISTRY.register()
class ToyBackBone(Backbone):
def __init__(self, cfg, input_shape):
# create your own backbone
self.conv1 = nn.Conv2d(3, 64, kernel_size=7, stride=16, padding=3)
def forward(self, image):
return {"conv1": self.conv1(image)}
def output_shape(self):
return {"conv1": ShapeSpec(channels=64, stride=16)}
Then, you can use cfg.MODEL.BACKBONE.NAME = 'ToyBackBone'
in your config object.
build_model(cfg)
will then call your ToyBackBone
instead.
As another example, to add new abilities to the ROI heads in the Generalized R-CNN meta-architecture,
you can implement a new
ROIHeads subclass and put it in the ROI_HEADS_REGISTRY
.
See densepose in detectron2
and meshrcnn
for examples that implement new ROIHeads to perform new tasks.
And projects/
contains more examples that implement different architectures.
A complete list of registries can be found in API documentation. You can register components in these registries to customize different parts of a model, or the entire model.