Update config.py
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config.py
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"""
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Mask R-CNN
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Base Configurations class.
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Copyright (c) 2017 Matterport, Inc.
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Licensed under the MIT License (see LICENSE for details)
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Written by Waleed Abdulla
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"""
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import numpy as np
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# Base Configuration Class
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# Don't use this class directly. Instead, sub-class it and override
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# the configurations you need to change.
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class Config(object):
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"""Base configuration class. For custom configurations, create a
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sub-class that inherits from this one and override properties
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that need to be changed.
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"""
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# Name the configurations. For example, 'COCO', 'Experiment 3', ...etc.
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# Useful if your code needs to do things differently depending on which
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# experiment is running.
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NAME = None # Override in sub-classes
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IMAGE_MIN_SCALE = 0
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# Number of color channels per image. RGB = 3, grayscale = 1, RGB-D = 4
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# Changing this requires other changes in the code. See the WIKI for more
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# details: https://github.com/matterport/Mask_RCNN/wiki
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IMAGE_CHANNEL_COUNT = 3
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# Image mean (RGB)
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LOSS_WEIGHTS = {
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"rpn_class_loss": 1.,
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"rpn_bbox_loss": 1.,
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"
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"
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"
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}
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# Use RPN ROIs or externally generated ROIs for training
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for a in dir(self):
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if not a.startswith("__") and not callable(getattr(self, a)):
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print("{:30} {}".format(a, getattr(self, a)))
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print("\n")
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import numpy as np
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class Config(object):
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# experiment is running.
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NAME = None # Override in sub-classes
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IMAGE_MIN_SCALE = 0
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# Number of color channels per image. RGB = 3, grayscale = 1, RGB-D = 4
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# Changing this requires other changes in the code. See the WIKI for more
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IMAGE_CHANNEL_COUNT = 3
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# Image mean (RGB)
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LOSS_WEIGHTS = {
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"rpn_class_loss": 1.,
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"rpn_bbox_loss": 1.,
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"bboxcnn_class_loss": 1.,
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"bboxcnn_bbox_loss": 1.,
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"bboxcnn_mask_loss": 1.
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}
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# Use RPN ROIs or externally generated ROIs for training
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for a in dir(self):
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if not a.startswith("__") and not callable(getattr(self, a)):
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print("{:30} {}".format(a, getattr(self, a)))
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print("\n")
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