2022-09-12 11:38:01 +02:00

114 lines
4.1 KiB
Python

import json
import math
import os
from functools import lru_cache
from operator import itemgetter
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
from funcy import filter, juxt, first, rest
logger = get_logger()
class ResponseTransformer(Transformer):
def transform(self, data):
logger.debug("ResponseTransformer.transform")
return build_image_info(data)
def build_image_info(data: dict) -> dict:
def compute_geometric_quotient():
page_area_sqrt = math.sqrt(abs(page_width * page_height))
image_area_sqrt = math.sqrt(abs(x2 - x1) * abs(y2 - y1))
return image_area_sqrt / page_area_sqrt
page_width, page_height, x1, x2, y1, y2, width, height, alpha = itemgetter(
"page_width", "page_height", "x1", "x2", "y1", "y2", "width", "height", "alpha"
)(data)
quotient = round(compute_geometric_quotient(), 4)
min_image_to_page_quotient_breached = bool(quotient < CONFIG.filters.image_to_page_quotient.min)
max_image_to_page_quotient_breached = __is_max_image_to_page_quotient_breached(
quotient, data["classification"]["label"]
)
min_image_width_to_height_quotient_breached = bool(
width / height < CONFIG.filters.image_width_to_height_quotient.min
)
max_image_width_to_height_quotient_breached = bool(
width / height > CONFIG.filters.image_width_to_height_quotient.max
)
classification = data["classification"]
representation = data["representation"]
min_confidence_breached = bool(max(classification["probabilities"].values()) < CONFIG.filters.min_confidence)
image_info = {
"classification": classification,
"representation": representation,
"position": {"x1": x1, "x2": x2, "y1": y1, "y2": y2, "pageNumber": data["page_idx"] + 1},
"geometry": {"width": width, "height": height},
"alpha": alpha,
"filters": {
"geometry": {
"imageSize": {
"quotient": quotient,
"tooLarge": max_image_to_page_quotient_breached,
"tooSmall": min_image_to_page_quotient_breached,
},
"imageFormat": {
"quotient": round(width / height, 4),
"tooTall": min_image_width_to_height_quotient_breached,
"tooWide": max_image_width_to_height_quotient_breached,
},
},
"probability": {"unconfident": min_confidence_breached},
"allPassed": not any(
[
max_image_to_page_quotient_breached,
min_image_to_page_quotient_breached,
min_image_width_to_height_quotient_breached,
max_image_width_to_height_quotient_breached,
min_confidence_breached,
]
),
},
}
return image_info
def __is_max_image_to_page_quotient_breached(quotient: float, label: str) -> bool:
default_max_quotient = CONFIG.filters.image_to_page_quotient.max
customized_entries = CONFIG.filters.image_to_page_quotient.customized.max
max_quotient = customized_entries.get(label, default_max_quotient)
max_quotient = max_quotient if max_quotient else default_max_quotient
return bool(quotient > max_quotient)
@lru_cache(maxsize=None)
def parse_env_var(prefix, fallback_value):
head, tail = juxt(first, rest)(filter(prefix, os.environ))
if not head or tail:
logger.warning(
f"Found multiple candidates for environment variable with prefix '{prefix}', falling back to default value."
)
return fallback_value
else:
try:
return parse_env_var_value(os.environ[head])
except ParsingError as err:
logger.warning(f"{err}, falling back to default value.")
return fallback_value
def parse_env_var_value(env_var_value):
try:
return json.loads(env_var_value)
except Exception as err:
raise ParsingError(f"Failed to parse {env_var_value}") from err