chore(prediction filters): adapt class specific filter logic

config/settings.toml

@@ -11,9 +11,9 @@ mlflow_run_id = "fabfb1f192c745369b88cab34471aba7"
 # The filter result values are reported in the service responses. For convenience the response to a request contains a
 # "filters.allPassed" field, which is set to false if any of the values returned by the filters did not meet its
 # specified required value.
-[filters]
+[filters.confidence]
 # Minimum permissible prediction confidence
-min_confidence = 0.5
+min = 0.5
 
 # Image size to page size ratio (ratio of geometric means of areas)
 [filters.image_to_page_quotient]
@@ -25,4 +25,8 @@ max = 0.75
 min = 0.1
 max = 10
 
+# put class specific filters here ['signature', 'formula', 'logo']
+[filters.overrides.signature.image_to_page_quotient]
+max = 0.4
+
 

pyproject.toml

@@ -1,6 +1,6 @@
 [tool.poetry]
 name = "image-classification-service"
-version = "2.0.0"
+version = "2.2.0"
 description = ""
 authors = ["Team Research <research@knecon.com>"]
 readme = "README.md"

src/image_prediction/transformer/transformers/response.py

@@ -1,13 +1,8 @@
-import json
 import math
-import os
+from dynaconf import Dynaconf
-from functools import lru_cache
 from operator import itemgetter
 
-from funcy import first
-
 from image_prediction.config import CONFIG
-from image_prediction.exceptions import ParsingError
 from image_prediction.transformer.transformer import Transformer
 from image_prediction.utils import get_logger
 
@@ -32,21 +27,22 @@ def build_image_info(data: dict) -> dict:
     geometric_quotient = round(compute_geometric_quotient(page_width, page_height, x2, x1, y2, y1), 4)
 
     min_image_to_page_quotient_breached = bool(
-        geometric_quotient < get_class_specific_min_image_to_page_quotient(label)
+        geometric_quotient < get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "min")
     )
     max_image_to_page_quotient_breached = bool(
-        geometric_quotient > get_class_specific_max_image_to_page_quotient(label)
+        geometric_quotient > get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "max")
     )
 
     min_image_width_to_height_quotient_breached = bool(
-        width / height < get_class_specific_min_image_width_to_height_quotient(label)
+        width / height < get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "min")
     )
     max_image_width_to_height_quotient_breached = bool(
-        width / height > get_class_specific_max_image_width_to_height_quotient(label)
+        width / height > get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "max")
     )
 
     min_confidence_breached = bool(
-        max(classification["probabilities"].values()) < get_class_specific_min_classification_confidence(label)
+        max(classification["probabilities"].values())
+        < get_class_specific_filter_value(label, CONFIG, "confidence", "min")
     )
 
     image_info = {
@@ -90,65 +86,15 @@ def compute_geometric_quotient(page_width, page_height, x2, x1, y2, y1):
     return image_area_sqrt / page_area_sqrt
 
 
-def get_class_specific_min_image_to_page_quotient(label, table=None):
+def get_class_specific_filter_value(label: str, settings: Dynaconf, filter_type: str, bound: str = None):
-    return get_class_specific_value(
-        "REL_IMAGE_SIZE", label, "min", CONFIG.filters.image_to_page_quotient.min, table=table
-    )
-
-
-def get_class_specific_max_image_to_page_quotient(label, table=None):
-    return get_class_specific_value(
-        "REL_IMAGE_SIZE", label, "max", CONFIG.filters.image_to_page_quotient.max, table=table
-    )
-
-
-def get_class_specific_min_image_width_to_height_quotient(label, table=None):
-    return get_class_specific_value(
-        "IMAGE_FORMAT", label, "min", CONFIG.filters.image_width_to_height_quotient.min, table=table
-    )
-
-
-def get_class_specific_max_image_width_to_height_quotient(label, table=None):
-    return get_class_specific_value(
-        "IMAGE_FORMAT", label, "max", CONFIG.filters.image_width_to_height_quotient.max, table=table
-    )
-
-
-def get_class_specific_min_classification_confidence(label, table=None):
-    return get_class_specific_value("CONFIDENCE", label, "min", CONFIG.filters.min_confidence, table=table)
-
-
-def get_class_specific_value(prefix, label, bound, fallback_value, table=None):
-    def fallback():
-        return fallback_value
-
-    def success():
-        threshold_map = parse_env_var(prefix, table=table) or {}
-        value = threshold_map.get(label, {}).get(bound)
-        if value:
-            logger.debug(f"Using class '{label}' specific {bound} {prefix.lower().replace('_', '-')} value.")
-        return value
-
-    assert bound in ["min", "max"]
-
-    return success() or fallback()
-
-
-@lru_cache(maxsize=None)
-def parse_env_var(prefix, table=None):
-    table = table or os.environ
-    head = first(filter(lambda s: s == prefix, table))
-    if head:
-        try:
-            return parse_env_var_value(table[head])
-        except ParsingError as err:
-            logger.warning(err)
-    else:
-        return None
-
-
-def parse_env_var_value(env_var_value):
     try:
-        return json.loads(env_var_value)
+        value = (
-    except Exception as err:
+            settings.filters.overrides[label][filter_type][bound]
-        raise ParsingError(f"Failed to parse {env_var_value}") from err
+            if bound
+            else settings.filters.overrides[label][filter_type]
+        )
+        logger.warning(f"Using {label=} specific {bound=} {filter_type=} {value=}.")
+    except KeyError:
+        value = settings.filters[filter_type][bound]
+
+    return value

test/unit_tests/response_transformer_test.py

@@ -1,15 +1,7 @@
-import json
-
 import pytest
-from frozendict import frozendict
 
-from image_prediction.transformer.transformers.response import (
+from image_prediction.config import CONFIG
-    get_class_specific_min_image_to_page_quotient,
+from image_prediction.transformer.transformers.response import get_class_specific_filter_value
-    get_class_specific_max_image_to_page_quotient,
-    get_class_specific_max_image_width_to_height_quotient,
-    get_class_specific_min_image_width_to_height_quotient,
-    get_class_specific_min_classification_confidence,
-)
 
 
 @pytest.fixture
@@ -17,20 +9,9 @@ def label():
     return "signature"
 
 
-@pytest.fixture
+def test_read_environment_vars_for_thresholds(label):
-def page_quotient_threshold_map(label):
+    assert get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "min") == 0.05
-    return frozendict(
+    assert get_class_specific_filter_value(label, CONFIG, "image_to_page_quotient", "max") == 0.4
-        {
+    assert get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "min") == 0.1
-            "REL_IMAGE_SIZE": json.dumps({label: {"min": 0.1, "max": 0.2}}),
+    assert get_class_specific_filter_value(label, CONFIG, "image_width_to_height_quotient", "max") == 10
-            "IMAGE_FORMAT": json.dumps({label: {"min": 0.5, "max": 0.4}}),
+    assert get_class_specific_filter_value(label, CONFIG, "confidence", "min") == 0.5
-            "CONFIDENCE": json.dumps({label: {"min": 0.8}}),
-        }
-    )
-
-
-def test_read_environment_vars_for_thresholds(page_quotient_threshold_map, label):
-    assert get_class_specific_min_image_to_page_quotient(label, table=page_quotient_threshold_map) == 0.1
-    assert get_class_specific_max_image_to_page_quotient(label, table=page_quotient_threshold_map) == 0.2
-    assert get_class_specific_min_image_width_to_height_quotient(label, table=page_quotient_threshold_map) == 0.5
-    assert get_class_specific_max_image_width_to_height_quotient(label, table=page_quotient_threshold_map) == 0.4
-    assert get_class_specific_min_classification_confidence(label, table=page_quotient_threshold_map) == 0.8