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refactor: module structure

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283375
2023-10-03 15:05:03 +08:00
parent 0d8e4dea8e
commit d5ccbd5a01
19 changed files with 517 additions and 525 deletions
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src/arcaea_offline_ocr/device/rois/masker/auto.py Normal file
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import cv2
import numpy as np
from .common import DeviceRoisMasker
class DeviceRoisMaskerAuto(DeviceRoisMasker):
...
class DeviceRoisMaskerAutoT1(DeviceRoisMaskerAuto):
GRAY_BGR_MIN = np.array([50] * 3, np.uint8)
GRAY_BGR_MAX = np.array([160] * 3, np.uint8)
WHITE_HSV_MIN = np.array([0, 0, 240], np.uint8)
WHITE_HSV_MAX = np.array([179, 10, 255], np.uint8)
PST_HSV_MIN = np.array([100, 50, 80], np.uint8)
PST_HSV_MAX = np.array([100, 255, 255], np.uint8)
PRS_HSV_MIN = np.array([43, 40, 75], np.uint8)
PRS_HSV_MAX = np.array([50, 155, 190], np.uint8)
FTR_HSV_MIN = np.array([149, 30, 0], np.uint8)
FTR_HSV_MAX = np.array([155, 181, 150], np.uint8)
BYD_HSV_MIN = np.array([170, 50, 50], np.uint8)
BYD_HSV_MAX = np.array([179, 210, 198], np.uint8)
TRACK_LOST_HSV_MIN = np.array([170, 75, 90], np.uint8)
TRACK_LOST_HSV_MAX = np.array([175, 170, 160], np.uint8)
TRACK_COMPLETE_HSV_MIN = np.array([140, 0, 50], np.uint8)
TRACK_COMPLETE_HSV_MAX = np.array([145, 50, 130], np.uint8)
FULL_RECALL_HSV_MIN = np.array([140, 60, 80], np.uint8)
FULL_RECALL_HSV_MAX = np.array([150, 130, 145], np.uint8)
PURE_MEMORY_HSV_MIN = np.array([90, 70, 80], np.uint8)
PURE_MEMORY_HSV_MAX = np.array([110, 200, 175], np.uint8)
@classmethod
def gray(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
bgr_value_equal_mask = np.max(roi_bgr, axis=2) - np.min(roi_bgr, axis=2) <= 5
img_bgr = roi_bgr.copy()
img_bgr[~bgr_value_equal_mask] = np.array([0, 0, 0], roi_bgr.dtype)
img_bgr = cv2.erode(img_bgr, cv2.getStructuringElement(cv2.MORPH_RECT, (2, 2)))
img_bgr = cv2.dilate(img_bgr, cv2.getStructuringElement(cv2.MORPH_RECT, (1, 1)))
return cv2.inRange(img_bgr, cls.GRAY_BGR_MIN, cls.GRAY_BGR_MAX)
@classmethod
def pure(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cls.gray(roi_bgr)
@classmethod
def far(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cls.gray(roi_bgr)
@classmethod
def lost(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cls.gray(roi_bgr)
@classmethod
def score(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.WHITE_HSV_MIN,
cls.WHITE_HSV_MAX,
)
@classmethod
def rating_class_pst(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.PST_HSV_MIN, cls.PST_HSV_MAX
)
@classmethod
def rating_class_prs(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.PRS_HSV_MIN, cls.PRS_HSV_MAX
)
@classmethod
def rating_class_ftr(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.FTR_HSV_MIN, cls.FTR_HSV_MAX
)
@classmethod
def rating_class_byd(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.BYD_HSV_MIN, cls.BYD_HSV_MAX
)
@classmethod
def max_recall(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cls.gray(roi_bgr)
@classmethod
def clear_status_track_lost(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.TRACK_LOST_HSV_MIN,
cls.TRACK_LOST_HSV_MAX,
)
@classmethod
def clear_status_track_complete(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.TRACK_COMPLETE_HSV_MIN,
cls.TRACK_COMPLETE_HSV_MAX,
)
@classmethod
def clear_status_full_recall(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.FULL_RECALL_HSV_MIN,
cls.FULL_RECALL_HSV_MAX,
)
@classmethod
def clear_status_pure_memory(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.PURE_MEMORY_HSV_MIN,
cls.PURE_MEMORY_HSV_MAX,
)
class DeviceRoisMaskerAutoT2(DeviceRoisMaskerAuto):
PFL_HSV_MIN = np.array([0, 0, 248], np.uint8)
PFL_HSV_MAX = np.array([179, 10, 255], np.uint8)
WHITE_HSV_MIN = np.array([0, 0, 240], np.uint8)
WHITE_HSV_MAX = np.array([179, 10, 255], np.uint8)
PST_HSV_MIN = np.array([100, 50, 80], np.uint8)
PST_HSV_MAX = np.array([100, 255, 255], np.uint8)
PRS_HSV_MIN = np.array([43, 40, 75], np.uint8)
PRS_HSV_MAX = np.array([50, 155, 190], np.uint8)
FTR_HSV_MIN = np.array([149, 30, 0], np.uint8)
FTR_HSV_MAX = np.array([155, 181, 150], np.uint8)
BYD_HSV_MIN = np.array([170, 50, 50], np.uint8)
BYD_HSV_MAX = np.array([179, 210, 198], np.uint8)
MAX_RECALL_HSV_MIN = np.array([125, 0, 0], np.uint8)
MAX_RECALL_HSV_MAX = np.array([130, 100, 150], np.uint8)
TRACK_LOST_HSV_MIN = np.array([170, 75, 90], np.uint8)
TRACK_LOST_HSV_MAX = np.array([175, 170, 160], np.uint8)
TRACK_COMPLETE_HSV_MIN = np.array([140, 0, 50], np.uint8)
TRACK_COMPLETE_HSV_MAX = np.array([145, 50, 130], np.uint8)
FULL_RECALL_HSV_MIN = np.array([140, 60, 80], np.uint8)
FULL_RECALL_HSV_MAX = np.array([150, 130, 145], np.uint8)
PURE_MEMORY_HSV_MIN = np.array([90, 70, 80], np.uint8)
PURE_MEMORY_HSV_MAX = np.array([110, 200, 175], np.uint8)
@classmethod
def pfl(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.PFL_HSV_MIN, cls.PFL_HSV_MAX
)
@classmethod
def pure(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cls.pfl(roi_bgr)
@classmethod
def far(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cls.pfl(roi_bgr)
@classmethod
def lost(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cls.pfl(roi_bgr)
@classmethod
def score(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.WHITE_HSV_MIN,
cls.WHITE_HSV_MAX,
)
@classmethod
def rating_class_pst(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.PST_HSV_MIN, cls.PST_HSV_MAX
)
@classmethod
def rating_class_prs(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.PRS_HSV_MIN, cls.PRS_HSV_MAX
)
@classmethod
def rating_class_ftr(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.FTR_HSV_MIN, cls.FTR_HSV_MAX
)
@classmethod
def rating_class_byd(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV), cls.BYD_HSV_MIN, cls.BYD_HSV_MAX
)
@classmethod
def max_recall(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.MAX_RECALL_HSV_MIN,
cls.MAX_RECALL_HSV_MAX,
)
@classmethod
def clear_status_track_lost(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.TRACK_LOST_HSV_MIN,
cls.TRACK_LOST_HSV_MAX,
)
@classmethod
def clear_status_track_complete(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.TRACK_COMPLETE_HSV_MIN,
cls.TRACK_COMPLETE_HSV_MAX,
)
@classmethod
def clear_status_full_recall(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.FULL_RECALL_HSV_MIN,
cls.FULL_RECALL_HSV_MAX,
)
@classmethod
def clear_status_pure_memory(cls, roi_bgr: cv2.Mat) -> cv2.Mat:
return cv2.inRange(
cv2.cvtColor(roi_bgr, cv2.COLOR_BGR2HSV),
cls.PURE_MEMORY_HSV_MIN,
cls.PURE_MEMORY_HSV_MAX,
)