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refactor: CropBlackEdges

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283375 2023-10-22 01:55:20 +08:00
parent 42bcd7b430
commit 122a546174
Signed by: 283375
SSH Key Fingerprint: SHA256:UcX0qg6ZOSDOeieKPGokA5h7soykG61nz2uxuQgVLSk
1 changed files with 45 additions and 84 deletions
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src/arcaea_offline_ocr/crop.py
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@ -1,10 +1,10 @@
from math import floor import math
from typing import Tuple from typing import Tuple
import cv2 import cv2
import numpy as np import numpy as np
__all__ = ["crop_xywh", "crop_black_edges", "crop_black_edges_grayscale"] __all__ = ["crop_xywh", "CropBlackEdges"]
def crop_xywh(mat: cv2.Mat, rect: Tuple[int, int, int, int]): def crop_xywh(mat: cv2.Mat, rect: Tuple[int, int, int, int]):
@ -12,92 +12,53 @@ def crop_xywh(mat: cv2.Mat, rect: Tuple[int, int, int, int]):
return mat[y : y + h, x : x + w] return mat[y : y + h, x : x + w]
def is_black_edge(list_of_pixels: cv2.Mat, black_pixel: cv2.Mat, ratio: float = 0.6): class CropBlackEdges:
pixels = list_of_pixels.reshape([-1, 3]) @staticmethod
return np.count_nonzero(np.all(pixels < black_pixel, axis=1)) > floor( def is_black_edge(__img_gray_slice: cv2.Mat, black_pixel: int, ratio: float = 0.6):
len(pixels) * ratio pixels_compared = __img_gray_slice < black_pixel
) return np.count_nonzero(pixels_compared) > math.floor(
__img_gray_slice.size * ratio
)
@classmethod
def get_crop_rect(cls, img_gray: cv2.Mat, black_threshold: int = 25):
height, width = img_gray.shape[:2]
left = 0
right = width
top = 0
bottom = height
def crop_black_edges(img_bgr: cv2.Mat, black_threshold: int = 50): for i in range(width):
cropped = img_bgr.copy() column = img_gray[:, i]
black_pixel = np.array([black_threshold] * 3, img_bgr.dtype) if not cls.is_black_edge(column, black_threshold):
height, width = img_bgr.shape[:2] break
left = 0 left += 1
right = width
top = 0
bottom = height
for i in range(width): for i in sorted(range(width), reverse=True):
column = cropped[:, i] column = img_gray[:, i]
if not is_black_edge(column, black_pixel): if i <= left + 1 or not cls.is_black_edge(column, black_threshold):
break break
left += 1 right -= 1
for i in sorted(range(width), reverse=True): for i in range(height):
column = cropped[:, i] row = img_gray[i]
if i <= left + 1 or not is_black_edge(column, black_pixel): if not cls.is_black_edge(row, black_threshold):
break break
right -= 1 top += 1
for i in range(height): for i in sorted(range(height), reverse=True):
row = cropped[i] row = img_gray[i]
if not is_black_edge(row, black_pixel): if i <= top + 1 or not cls.is_black_edge(row, black_threshold):
break break
top += 1 bottom -= 1
for i in sorted(range(height), reverse=True): assert right > left, "cropped width < 0"
row = cropped[i] assert bottom > top, "cropped height < 0"
if i <= top + 1 or not is_black_edge(row, black_pixel): return (left, top, right - left, bottom - top)
break
bottom -= 1
return cropped[top:bottom, left:right] @classmethod
def crop(
cls, img: cv2.Mat, convert_flag: cv2.COLOR_BGR2GRAY, black_threshold: int = 25
def is_black_edge_grayscale( ) -> cv2.Mat:
gray_value_list: np.ndarray, black_threshold: int = 50, ratio: float = 0.6 rect = cls.get_crop_rect(cv2.cvtColor(img, convert_flag), black_threshold)
) -> bool: return crop_xywh(img, rect)
return (
np.count_nonzero(gray_value_list < black_threshold)
> len(gray_value_list) * ratio
)
def crop_black_edges_grayscale(
img_gray: cv2.Mat, black_threshold: int = 50
) -> Tuple[int, int, int, int]:
"""Returns cropped rect"""
height, width = img_gray.shape[:2]
left = 0
right = width
top = 0
bottom = height
for i in range(width):
column = img_gray[:, i]
if not is_black_edge_grayscale(column, black_threshold):
break
left += 1
for i in sorted(range(width), reverse=True):
column = img_gray[:, i]
if i <= left + 1 or not is_black_edge_grayscale(column, black_threshold):
break
right -= 1
for i in range(height):
row = img_gray[i]
if not is_black_edge_grayscale(row, black_threshold):
break
top += 1
for i in sorted(range(height), reverse=True):
row = img_gray[i]
if i <= top + 1 or not is_black_edge_grayscale(row, black_threshold):
break
bottom -= 1
assert right > left, "cropped width > 0"
assert bottom > top, "cropped height > 0"
return (left, top, right - left, bottom - top)