cleanlab--cleanlab
Yiran Shi
902fb487c9
Add dataset summary functions+plots to object detection. --------- Co-authored-by: Jonas Mueller <1390638+jwmueller@users.noreply.github.com> Co-authored-by: Ulyana <ulyana@cleanlab.ai>
56 行
4.0 KiB
Python
56 行
4.0 KiB
Python
# Copyright (C) 2017-2023 Cleanlab Inc.
|
|
# This file is part of cleanlab.
|
|
#
|
|
# cleanlab is free software: you can redistribute it and/or modify
|
|
# it under the terms of the GNU Affero General Public License as published
|
|
# by the Free Software Foundation, either version 3 of the License, or
|
|
# (at your option) any later version.
|
|
#
|
|
# cleanlab is distributed in the hope that it will be useful,
|
|
# but WITHOUT ANY WARRANTY; without even the implied warranty of
|
|
# MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
|
|
# GNU Affero General Public License for more details.
|
|
#
|
|
# You should have received a copy of the GNU Affero General Public License
|
|
# along with cleanlab. If not, see <https://www.gnu.org/licenses/>.
|
|
|
|
|
|
FLOATING_POINT_COMPARISON = 1e-6 # floating point comparison for fuzzy equals
|
|
CLIPPING_LOWER_BOUND = 1e-6 # lower-bound clipping threshold for expected behavior
|
|
CONFIDENT_THRESHOLDS_LOWER_BOUND = (
|
|
2 * FLOATING_POINT_COMPARISON
|
|
) # lower bound imposed to clip confident thresholds from below, has to be larger than floating point comparison
|
|
TINY_VALUE = 1e-100 # very tiny value for clipping
|
|
|
|
|
|
# Object Detection Constants
|
|
EUC_FACTOR = 0.1 # Factor to control magnitude of euclidian distance. Increasing the factor makes the distances between two objects go to zero more rapidly.
|
|
MAX_ALLOWED_BOX_PRUNE = 0.97 # This is max allowed percent of boxes that are pruned before a warning is thrown given a specific threshold. Pruning too many boxes negatively affects performance.
|
|
IOU_THRESHOLD = (
|
|
0.5 # Threshold for considering the predicted box and annotated box to be overlapping
|
|
)
|
|
EPSILON = 1e-6 # Small value to prevent division by zero
|
|
|
|
ALPHA = 0.9 # Param for objectlab, weight between IoU and distance when considering similarity matrix. High alpha means considering IoU more strongly over distance
|
|
LOW_PROBABILITY_THRESHOLD = 0.5 # Param for get_label_quality_score, lowest predicted class probability threshold allowed when considering predicted boxes to identify badly located label boxes.
|
|
HIGH_PROBABILITY_THRESHOLD = 0.95 # Param for objectlab, high probability threshold for considering predicted boxes to identify overlooked and swapped label boxes
|
|
TEMPERATURE = 0.1 # Param for objectlab, temperature of the softmin function used to pool the per-box quality scores for an error subtype across all boxes into a single subtype score for the image. With a lower temperature, softmin pooling acts more like minimum pooling, alternatively it acts more like mean pooling with high temperature.
|
|
LABEL_OVERLAP_THRESHOLD = 0.95 # Param for objectlab, minimum IoU threshold for deciding when two boxes overlap used for deciding which objects have multiple conflicting annotations.
|
|
|
|
OVERLOOKED_THRESHOLD_FACTOR = 0.8 # Param for find_label_issues. Per-box label quality score threshold scale factor to determine max score for a box to be considered an overlooked issue
|
|
BADLOC_THRESHOLD_FACTOR = 0.8 # Param for find_label_issues. Per-box label quality score threshold scale factor to determine max score for a box to be considered a bad location issue
|
|
SWAP_THRESHOLD_FACTOR = 0.8 # Param for find_label_issues. Per-box label quality score threshold scale factor to determine max score for a box to be considered a swap issue
|
|
AP_SCALE_FACTOR = 0.25 # Param for find_label_issues. Scale factor for per-class precision to determine is_issue.
|
|
|
|
CUSTOM_SCORE_WEIGHT_OVERLOOKED = (
|
|
1 / 3
|
|
) # Param for get_label_quality_score, weight to determine how much to value overlooked scores over other subtypes when deciding the overall label quality score for an image.
|
|
CUSTOM_SCORE_WEIGHT_BADLOC = (
|
|
1 / 3
|
|
) # Param for get_label_quality_score, weight to determine how much to value badloc scores over other subtypes when deciding issues
|
|
CUSTOM_SCORE_WEIGHT_SWAP = (
|
|
1 / 3
|
|
) # Param for get_label_quality_score, weight to determine how much to value swap scores over other subtypes when deciding issues
|
|
|
|
MAX_CLASS_TO_SHOW = 10 # Number of classes to show in legend during the visualize method. Classes over max_class_to_show are cut off.
|