chore(prediction filters): adapt class specific filter logic
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Julius Unverfehrt
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a024ddfcf7
commit
150d0d64e5
@ -11,9 +11,9 @@ mlflow_run_id = "fabfb1f192c745369b88cab34471aba7"
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# The filter result values are reported in the service responses. For convenience the response to a request contains a
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# "filters.allPassed" field, which is set to false if any of the values returned by the filters did not meet its
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# specified required value.
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[filters]
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[filters.confidence]
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# Minimum permissible prediction confidence
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min_confidence = 0.5
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min = 0.5
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# Image size to page size ratio (ratio of geometric means of areas)
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[filters.image_to_page_quotient]
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@ -25,4 +25,8 @@ max = 0.75
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min = 0.1
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max = 10
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# put class specific filters here ['signature', 'formula', 'logo']
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[filters.overrides.signature.image_to_page_quotient]
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max = 0.4
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@ -1,6 +1,6 @@
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[tool.poetry]
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name = "image-classification-service"
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version = "2.0.0"
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version = "2.2.0"
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description = ""
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authors = ["Team Research <research@knecon.com>"]
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readme = "README.md"
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@ -1,13 +1,8 @@
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import json
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import math
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import os
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from functools import lru_cache
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from dynaconf import Dynaconf
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from operator import itemgetter
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from funcy import first
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from image_prediction.config import CONFIG
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from image_prediction.exceptions import ParsingError
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from image_prediction.transformer.transformer import Transformer
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from image_prediction.utils import get_logger
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@ -32,21 +27,22 @@ def build_image_info(data: dict) -> dict:
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geometric_quotient = round(compute_geometric_quotient(page_width, page_height, x2, x1, y2, y1), 4)
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min_image_to_page_quotient_breached = bool(
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geometric_quotient < get_class_specific_min_image_to_page_quotient(label)
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geometric_quotient < get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "min")
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)
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max_image_to_page_quotient_breached = bool(
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geometric_quotient > get_class_specific_max_image_to_page_quotient(label)
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geometric_quotient > get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "max")
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)
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min_image_width_to_height_quotient_breached = bool(
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width / height < get_class_specific_min_image_width_to_height_quotient(label)
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width / height < get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "min")
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)
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max_image_width_to_height_quotient_breached = bool(
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width / height > get_class_specific_max_image_width_to_height_quotient(label)
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width / height > get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "max")
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)
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min_confidence_breached = bool(
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max(classification["probabilities"].values()) < get_class_specific_min_classification_confidence(label)
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max(classification["probabilities"].values())
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< get_class_specific_filter_value(label, CONFIG, "confidence", "min")
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)
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image_info = {
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@ -90,65 +86,15 @@ def compute_geometric_quotient(page_width, page_height, x2, x1, y2, y1):
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return image_area_sqrt / page_area_sqrt
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def get_class_specific_min_image_to_page_quotient(label, table=None):
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return get_class_specific_value(
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"REL_IMAGE_SIZE", label, "min", CONFIG.filters.image_to_page_quotient.min, table=table
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)
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def get_class_specific_max_image_to_page_quotient(label, table=None):
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return get_class_specific_value(
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"REL_IMAGE_SIZE", label, "max", CONFIG.filters.image_to_page_quotient.max, table=table
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)
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def get_class_specific_min_image_width_to_height_quotient(label, table=None):
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return get_class_specific_value(
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"IMAGE_FORMAT", label, "min", CONFIG.filters.image_width_to_height_quotient.min, table=table
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)
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def get_class_specific_max_image_width_to_height_quotient(label, table=None):
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return get_class_specific_value(
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"IMAGE_FORMAT", label, "max", CONFIG.filters.image_width_to_height_quotient.max, table=table
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)
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def get_class_specific_min_classification_confidence(label, table=None):
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return get_class_specific_value("CONFIDENCE", label, "min", CONFIG.filters.min_confidence, table=table)
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def get_class_specific_value(prefix, label, bound, fallback_value, table=None):
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def fallback():
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return fallback_value
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def success():
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threshold_map = parse_env_var(prefix, table=table) or {}
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value = threshold_map.get(label, {}).get(bound)
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if value:
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logger.debug(f"Using class '{label}' specific {bound} {prefix.lower().replace('_', '-')} value.")
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return value
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assert bound in ["min", "max"]
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return success() or fallback()
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@lru_cache(maxsize=None)
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def parse_env_var(prefix, table=None):
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table = table or os.environ
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head = first(filter(lambda s: s == prefix, table))
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if head:
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try:
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return parse_env_var_value(table[head])
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except ParsingError as err:
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logger.warning(err)
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else:
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return None
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def parse_env_var_value(env_var_value):
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def get_class_specific_filter_value(label: str, settings: Dynaconf, filter_type: str, bound: str = None):
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try:
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return json.loads(env_var_value)
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except Exception as err:
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raise ParsingError(f"Failed to parse {env_var_value}") from err
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value = (
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settings.filters.overrides[label][filter_type][bound]
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if bound
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else settings.filters.overrides[label][filter_type]
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)
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logger.warning(f"Using {label=} specific {bound=} {filter_type=} {value=}.")
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except KeyError:
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value = settings.filters[filter_type][bound]
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return value
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@ -1,15 +1,7 @@
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import json
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import pytest
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from frozendict import frozendict
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from image_prediction.transformer.transformers.response import (
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get_class_specific_min_image_to_page_quotient,
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get_class_specific_max_image_to_page_quotient,
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get_class_specific_max_image_width_to_height_quotient,
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get_class_specific_min_image_width_to_height_quotient,
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get_class_specific_min_classification_confidence,
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)
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from image_prediction.config import CONFIG
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from image_prediction.transformer.transformers.response import get_class_specific_filter_value
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@pytest.fixture
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@ -17,20 +9,9 @@ def label():
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return "signature"
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@pytest.fixture
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def page_quotient_threshold_map(label):
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return frozendict(
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{
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"REL_IMAGE_SIZE": json.dumps({label: {"min": 0.1, "max": 0.2}}),
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"IMAGE_FORMAT": json.dumps({label: {"min": 0.5, "max": 0.4}}),
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"CONFIDENCE": json.dumps({label: {"min": 0.8}}),
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}
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)
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def test_read_environment_vars_for_thresholds(page_quotient_threshold_map, label):
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assert get_class_specific_min_image_to_page_quotient(label, table=page_quotient_threshold_map) == 0.1
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assert get_class_specific_max_image_to_page_quotient(label, table=page_quotient_threshold_map) == 0.2
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assert get_class_specific_min_image_width_to_height_quotient(label, table=page_quotient_threshold_map) == 0.5
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assert get_class_specific_max_image_width_to_height_quotient(label, table=page_quotient_threshold_map) == 0.4
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assert get_class_specific_min_classification_confidence(label, table=page_quotient_threshold_map) == 0.8
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def test_read_environment_vars_for_thresholds(label):
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assert get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "min") == 0.05
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assert get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "max") == 0.4
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assert get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "min") == 0.1
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assert get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "max") == 10
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assert get_class_specific_filter_value(label, CONFIG, "confidence", "min") == 0.5
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