StarRailCopilot/module/ocr/ocr.py

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Python
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import re
import time
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from datetime import timedelta
from typing import Optional
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import cv2
import numpy as np
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from pponnxcr.predict_system import BoxedResult
import module.config.server as server
from module.base.button import ButtonWrapper
from module.base.decorator import cached_property
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from module.base.utils import area_pad, corner2area, crop, extract_white_letters, float2str
from module.exception import ScriptError
from module.logger import logger
from module.ocr.keyword import Keyword
from module.ocr.models import OCR_MODEL, TextSystem
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from module.ocr.utils import merge_buttons
class OcrResultButton:
def __init__(self, boxed_result: BoxedResult, matched_keyword: Optional[Keyword]):
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"""
Args:
boxed_result: BoxedResult from ppocr-onnx
matched_keyword: Keyword object or None
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"""
self.area = boxed_result.box
self.search = area_pad(self.area, pad=-20)
# self.color =
self.button = boxed_result.box
if matched_keyword is not None:
self.matched_keyword = matched_keyword
self.name = str(matched_keyword)
else:
self.matched_keyword = None
self.name = boxed_result.ocr_text
self.text = boxed_result.ocr_text
self.score = boxed_result.score
def __str__(self):
return self.name
__repr__ = __str__
def __eq__(self, other):
return str(self) == str(other)
def __hash__(self):
return hash(self.name)
def __bool__(self):
return True
@property
def is_keyword_matched(self) -> bool:
return self.matched_keyword is not None
class Ocr:
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# Merge results with box distance <= thres
merge_thres_x = 0
merge_thres_y = 0
def __init__(self, button: ButtonWrapper, lang=None, name=None):
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"""
Args:
button:
lang: If None, use in-game language
name: If None, use button.name
"""
if lang is None:
lang = server.lang
if name is None:
name = button.name
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self.button: ButtonWrapper = button
self.lang: str = lang
self.name: str = name
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@cached_property
def model(self) -> TextSystem:
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return OCR_MODEL.get_by_lang(self.lang)
def pre_process(self, image):
"""
Args:
image (np.ndarray): Shape (height, width, channel)
Returns:
np.ndarray: Shape (width, height)
"""
return image
def after_process(self, result):
"""
Args:
result (str): '第二行'
Returns:
str:
"""
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if result.startswith('UID'):
result = 'UID'
return result
def format_result(self, result):
"""
Will be overriden.
"""
return result
def _log_change(self, attr, func, before):
after = func(before)
if after != before:
logger.attr(f'{self.name} {attr}', f'{before} -> {after}')
return after
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def ocr_single_line(self, image, direct_ocr=False):
# pre process
start_time = time.time()
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if not direct_ocr:
image = crop(image, self.button.area)
image = self.pre_process(image)
# ocr
result, _ = self.model.ocr_single_line(image)
# after proces
result = self._log_change('after', self.after_process, result)
result = self._log_change('format', self.format_result, result)
logger.attr(name='%s %ss' % (self.name, float2str(time.time() - start_time)),
text=str(result))
return result
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def ocr_multi_lines(self, image_list):
# pre process
start_time = time.time()
image_list = [self.pre_process(image) for image in image_list]
# ocr
result_list = self.model.ocr_lines(image_list)
result_list = [(result, score) for result, score in result_list]
# after process
result_list = [(self.after_process(result), score) for result, score in result_list]
result_list = [(self.format_result(result), score) for result, score in result_list]
logger.attr(name="%s %ss" % (self.name, float2str(time.time() - start_time)),
text=str([result for result, _ in result_list]))
return result_list
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def filter_detected(self, result: BoxedResult) -> bool:
"""
Return False to drop result.
"""
return True
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def detect_and_ocr(self, image, direct_ocr=False) -> list[BoxedResult]:
"""
Args:
image:
direct_ocr: True to ignore `button` attribute and feed the image to OCR model without cropping.
Returns:
"""
# pre process
start_time = time.time()
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if not direct_ocr:
image = crop(image, self.button.area)
image = self.pre_process(image)
# ocr
results: list[BoxedResult] = self.model.detect_and_ocr(image)
# after proces
for result in results:
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if not direct_ocr:
result.box += self.button.area[:2]
result.box = tuple(corner2area(result.box))
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results = [result for result in results if self.filter_detected(result)]
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results = merge_buttons(results, thres_x=self.merge_thres_x, thres_y=self.merge_thres_y)
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for result in results:
result.ocr_text = self.after_process(result.ocr_text)
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logger.attr(name='%s %ss' % (self.name, float2str(time.time() - start_time)),
text=str([result.ocr_text for result in results]))
return results
def _match_result(
self,
result: str,
keyword_classes,
lang: str = None,
ignore_punctuation=True,
ignore_digit=True):
"""
Args:
result (str):
keyword_classes: A list of `Keyword` class or classes inherited `Keyword`
Returns:
If matched, return `Keyword` object or objects inherited `Keyword`
If not match, return None
"""
if not isinstance(keyword_classes, list):
keyword_classes = [keyword_classes]
# Digits will be considered as the index of keyword
if ignore_digit:
if result.isdigit():
return None
# Try in current lang
for keyword_class in keyword_classes:
try:
matched = keyword_class.find(
result,
lang=lang,
ignore_punctuation=ignore_punctuation
)
return matched
except ScriptError:
continue
return None
def matched_single_line(
self,
image,
keyword_classes,
lang: str = None,
ignore_punctuation=True
) -> OcrResultButton:
"""
Args:
image: Image to detect
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keyword_classes: `Keyword` class or classes inherited `Keyword`, or a list of them.
lang:
ignore_punctuation:
Returns:
OcrResultButton: Or None if it didn't matched known keywords.
"""
result = self.ocr_single_line(image)
result = self._match_result(
result,
keyword_classes=keyword_classes,
lang=lang,
ignore_punctuation=ignore_punctuation,
)
logger.attr(name=f'{self.name} matched',
text=result)
return result
def matched_multi_lines(
self,
image_list,
keyword_classes,
lang: str = None,
ignore_punctuation=True
) -> list[OcrResultButton]:
"""
Args:
image_list:
keyword_classes: `Keyword` class or classes inherited `Keyword`, or a list of them.
lang:
ignore_punctuation:
Returns:
List of matched OcrResultButton.
OCR result which didn't matched known keywords will be dropped.
"""
results = self.ocr_multi_lines(image_list)
results = [self._match_result(
result,
keyword_classes=keyword_classes,
lang=lang,
ignore_punctuation=ignore_punctuation,
) for result in results]
results = [result for result in results if result.is_keyword_matched]
logger.attr(name=f'{self.name} matched',
text=results)
return results
def _product_button(
self,
boxed_result: BoxedResult,
keyword_classes,
lang: str = None,
ignore_punctuation=True,
ignore_digit=True
) -> OcrResultButton:
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if not isinstance(keyword_classes, list):
keyword_classes = [keyword_classes]
matched_keyword = self._match_result(
boxed_result.ocr_text,
keyword_classes=keyword_classes,
lang=lang,
ignore_punctuation=ignore_punctuation,
ignore_digit=ignore_digit,
)
button = OcrResultButton(boxed_result, matched_keyword)
return button
def matched_ocr(self, image, keyword_classes, direct_ocr=False) -> list[OcrResultButton]:
"""
Args:
image: Screenshot
keyword_classes: `Keyword` class or classes inherited `Keyword`, or a list of them.
direct_ocr: True to ignore `button` attribute and feed the image to OCR model without cropping.
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Returns:
List of matched OcrResultButton.
OCR result which didn't matched known keywords will be dropped.
"""
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results = self.detect_and_ocr(image, direct_ocr=direct_ocr)
results = [self._product_button(result, keyword_classes) for result in results]
results = [result for result in results if result.is_keyword_matched]
logger.attr(name=f'{self.name} matched',
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text=results)
return results
class Digit(Ocr):
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def __init__(self, button: ButtonWrapper, lang='en', name=None):
super().__init__(button, lang=lang, name=name)
def format_result(self, result) -> int:
"""
Returns:
int:
"""
result = super().after_process(result)
logger.attr(name=self.name, text=str(result))
res = re.search(r'(\d+)', result)
if res:
return int(res.group(1))
else:
logger.warning(f'No digit found in {result}')
return 0
class DigitCounter(Ocr):
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def __init__(self, button: ButtonWrapper, lang='en', name=None):
super().__init__(button, lang=lang, name=name)
def format_result(self, result) -> tuple[int, int, int]:
"""
Do OCR on a counter, such as `14/15`, and returns 14, 1, 15
Returns:
int:
"""
result = super().after_process(result)
logger.attr(name=self.name, text=str(result))
res = re.search(r'(\d+)/(\d+)', result)
if res:
groups = [int(s) for s in res.groups()]
current, total = int(groups[0]), int(groups[1])
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# current = min(current, total)
return current, total - current, total
else:
logger.warning(f'No digit counter found in {result}')
return 0, 0, 0
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class Duration(Ocr):
@classmethod
def timedelta_regex(cls, lang):
regex_str = {
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'cn': r'^(?P<prefix>.*?)'
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r'((?P<days>\d{1,2})\s*天\s*)?'
r'((?P<hours>\d{1,2})\s*小时\s*)?'
r'((?P<minutes>\d{1,2})\s*分钟\s*)?'
r'((?P<seconds>\d{1,2})\s*秒)?'
r'(?P<suffix>[^天时钟秒]*?)$',
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'en': r'^(?P<prefix>.*?)'
r'((?P<days>\d{1,2})\s*d\s*)?'
r'((?P<hours>\d{1,2})\s*h\s*)?'
r'((?P<minutes>\d{1,2})\s*m\s*)?'
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r'((?P<seconds>\d{1,2})\s*s)?'
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r'(?P<suffix>[^dhms]*?)$'
}[lang]
return re.compile(regex_str)
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def after_process(self, result):
result = super().after_process(result)
result = result.strip('.,。,')
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result = result.replace('Oh', '0h').replace('oh', '0h')
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return result
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def format_result(self, result: str) -> timedelta:
"""
Do OCR on a duration, such as `18d 2h 13m 30s`, `2h`, `13m 30s`, `9s`
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Returns:
timedelta:
"""
matched = self.timedelta_regex(self.lang).search(result)
if not matched:
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return timedelta()
days = self._sanitize_number(matched.group('days'))
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hours = self._sanitize_number(matched.group('hours'))
minutes = self._sanitize_number(matched.group('minutes'))
seconds = self._sanitize_number(matched.group('seconds'))
return timedelta(days=days, hours=hours, minutes=minutes, seconds=seconds)
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@staticmethod
def _sanitize_number(number) -> int:
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if number is None:
return 0
return int(number)
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class OcrWhiteLetterOnComplexBackground(Ocr):
def pre_process(self, image):
image = extract_white_letters(image, threshold=255)
image = cv2.merge([image, image, image])
return image
def detect_and_ocr(self, *args, **kwargs):
# Try hard to lower TextSystem.box_thresh
backup = self.model.text_detector.box_thresh
self.model.text_detector.box_thresh = 0.2
result = super().detect_and_ocr(*args, **kwargs)
self.model.text_detector.box_thresh = backup
return result