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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,14 +1,14 @@ | ||
| root = true | ||
|
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| [*] | ||
| end_of_line = lf | ||
| insert_final_newline = true | ||
| charset = utf-8 | ||
| indent_style = space | ||
| indent_size = 2 | ||
|
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| [*.py] | ||
| indent_size = 4 | ||
|
|
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| [*.ui] | ||
| indent_size = 1 | ||
| root = true | ||
|
|
||
| [*] | ||
| end_of_line = lf | ||
| insert_final_newline = true | ||
| charset = utf-8 | ||
| indent_style = space | ||
| indent_size = 2 | ||
|
|
||
| [*.py] | ||
| indent_size = 4 | ||
|
|
||
| [*.ui] | ||
| indent_size = 1 |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -0,0 +1,9 @@ | ||
| # Normalize EOF | ||
| * autocrlf=false | ||
| * eol=lf | ||
| *.png eol=auto | ||
| *.gif eol=auto | ||
| *.ico eol=auto | ||
| # Set linguist-language to support comments syntax highlight | ||
| pyrightconfig*.json linguist-language=jsonc | ||
| .vscode/*.json linguist-language=jsonc |
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| Original file line number | Diff line number | Diff line change |
|---|---|---|
| @@ -1,165 +1,165 @@ | ||
| import os | ||
| from enum import IntEnum, auto | ||
| from math import sqrt | ||
| from typing import TYPE_CHECKING | ||
|
|
||
| import cv2 | ||
| import numpy as np | ||
| from cv2.typing import MatLike | ||
|
|
||
| import error_messages | ||
| from compare import check_if_image_has_transparency, get_comparison_method_by_index | ||
| from utils import BGR_CHANNEL_COUNT, MAXBYTE, ColorChannel, ImageShape, is_valid_image | ||
|
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||
| if TYPE_CHECKING: | ||
| from AutoSplit import AutoSplit | ||
|
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|
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| # Resize to these width and height so that FPS performance increases | ||
| COMPARISON_RESIZE_WIDTH = 320 | ||
| COMPARISON_RESIZE_HEIGHT = 240 | ||
| COMPARISON_RESIZE = (COMPARISON_RESIZE_WIDTH, COMPARISON_RESIZE_HEIGHT) | ||
| COMPARISON_RESIZE_AREA = COMPARISON_RESIZE_WIDTH * COMPARISON_RESIZE_HEIGHT | ||
| MASK_LOWER_BOUND = np.array([0, 0, 0, 1], dtype="uint8") | ||
| MASK_UPPER_BOUND = np.array([MAXBYTE, MAXBYTE, MAXBYTE, MAXBYTE], dtype="uint8") | ||
| START_KEYWORD = "start_auto_splitter" | ||
| RESET_KEYWORD = "reset" | ||
|
|
||
|
|
||
| class ImageType(IntEnum): | ||
| SPLIT = auto() | ||
| RESET = auto() | ||
| START = auto() | ||
|
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||
|
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| class AutoSplitImage: | ||
| path: str | ||
| filename: str | ||
| flags: int | ||
| loops: int | ||
| image_type: ImageType | ||
| byte_array: MatLike | None = None | ||
| mask: MatLike | None = None | ||
| # This value is internal, check for mask instead | ||
| _has_transparency = False | ||
| # These values should be overriden by some Defaults if None. Use getters instead | ||
| __delay_time: float | None = None | ||
| __comparison_method: int | None = None | ||
| __pause_time: float | None = None | ||
| __similarity_threshold: float | None = None | ||
|
|
||
| def get_delay_time(self, default: "AutoSplit | int"): | ||
| """Get image's delay time or fallback to the default value from spinbox.""" | ||
| if self.__delay_time is not None: | ||
| return self.__delay_time | ||
| if isinstance(default, int): | ||
| return default | ||
| return default.settings_dict["default_delay_time"] | ||
|
|
||
| def __get_comparison_method_index(self, default: "AutoSplit | int"): | ||
| """Get image's comparison or fallback to the default value from combobox.""" | ||
| if self.__comparison_method is not None: | ||
| return self.__comparison_method | ||
| if isinstance(default, int): | ||
| return default | ||
| return default.settings_dict["default_comparison_method"] | ||
|
|
||
| def get_pause_time(self, default: "AutoSplit | float"): | ||
| """Get image's pause time or fallback to the default value from spinbox.""" | ||
| if self.__pause_time is not None: | ||
| return self.__pause_time | ||
| if isinstance(default, (float, int)): | ||
| return default | ||
| return default.settings_dict["default_pause_time"] | ||
|
|
||
| def get_similarity_threshold(self, default: "AutoSplit | float"): | ||
| """Get image's similarity threshold or fallback to the default value from spinbox.""" | ||
| if self.__similarity_threshold is not None: | ||
| return self.__similarity_threshold | ||
| if isinstance(default, (float, int)): | ||
| return default | ||
| return default.settings_dict["default_similarity_threshold"] | ||
|
|
||
| def __init__(self, path: str): | ||
| self.path = path | ||
| self.filename = os.path.split(path)[-1].lower() | ||
| self.flags = flags_from_filename(self.filename) | ||
| self.loops = loop_from_filename(self.filename) | ||
| self.__delay_time = delay_time_from_filename(self.filename) | ||
| self.__comparison_method = comparison_method_from_filename(self.filename) | ||
| self.__pause_time = pause_from_filename(self.filename) | ||
| self.__similarity_threshold = threshold_from_filename(self.filename) | ||
| self.__read_image_bytes(path) | ||
|
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| if START_KEYWORD in self.filename: | ||
| self.image_type = ImageType.START | ||
| elif RESET_KEYWORD in self.filename: | ||
| self.image_type = ImageType.RESET | ||
| else: | ||
| self.image_type = ImageType.SPLIT | ||
|
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||
| def __read_image_bytes(self, path: str): | ||
| image = cv2.imread(path, cv2.IMREAD_UNCHANGED) | ||
| if not is_valid_image(image): | ||
| self.byte_array = None | ||
| error_messages.image_type(path) | ||
| return | ||
|
|
||
| self._has_transparency = check_if_image_has_transparency(image) | ||
| # If image has transparency, create a mask | ||
| if self._has_transparency: | ||
| # Adaptively determine the target size according to | ||
| # the number of nonzero elements in the alpha channel of the split image. | ||
| # This may result in images bigger than COMPARISON_RESIZE if there's plenty of transparency. | ||
| # Which wouldn't incur any performance loss in methods where masked regions are ignored. | ||
| scale = min(1, sqrt(COMPARISON_RESIZE_AREA / cv2.countNonZero(image[:, :, ColorChannel.Alpha]))) | ||
|
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||
| image = cv2.resize( | ||
| image, | ||
| dsize=None, | ||
| fx=scale, | ||
| fy=scale, | ||
| interpolation=cv2.INTER_NEAREST, | ||
| ) | ||
|
|
||
| # Mask based on adaptively resized, nearest neighbor interpolated split image | ||
| self.mask = cv2.inRange(image, MASK_LOWER_BOUND, MASK_UPPER_BOUND) | ||
| else: | ||
| image = cv2.resize(image, COMPARISON_RESIZE, interpolation=cv2.INTER_NEAREST) | ||
| # Add Alpha channel if missing | ||
| if image.shape[ImageShape.Channels] == BGR_CHANNEL_COUNT: | ||
| image = cv2.cvtColor(image, cv2.COLOR_BGR2BGRA) | ||
|
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| self.byte_array = image | ||
|
|
||
| def check_flag(self, flag: int): | ||
| return self.flags & flag == flag | ||
|
|
||
| def compare_with_capture( | ||
| self, | ||
| default: "AutoSplit | int", | ||
| capture: MatLike | None, | ||
| ): | ||
| """Compare image with capture using image's comparison method. Falls back to combobox.""" | ||
| if not is_valid_image(self.byte_array) or not is_valid_image(capture): | ||
| return 0.0 | ||
| resized_capture = cv2.resize(capture, self.byte_array.shape[1::-1]) | ||
|
|
||
| return get_comparison_method_by_index( | ||
| self.__get_comparison_method_index(default), | ||
| )( | ||
| self.byte_array, | ||
| resized_capture, | ||
| self.mask, | ||
| ) | ||
|
|
||
|
|
||
| if True: | ||
| from split_parser import ( | ||
| comparison_method_from_filename, | ||
| delay_time_from_filename, | ||
| flags_from_filename, | ||
| loop_from_filename, | ||
| pause_from_filename, | ||
| threshold_from_filename, | ||
| ) | ||
| import os | ||
| from enum import IntEnum, auto | ||
| from math import sqrt | ||
| from typing import TYPE_CHECKING | ||
|
|
||
| import cv2 | ||
| import numpy as np | ||
| from cv2.typing import MatLike | ||
|
|
||
| import error_messages | ||
| from compare import check_if_image_has_transparency, get_comparison_method_by_index | ||
| from utils import BGR_CHANNEL_COUNT, MAXBYTE, ColorChannel, ImageShape, is_valid_image | ||
|
|
||
| if TYPE_CHECKING: | ||
| from AutoSplit import AutoSplit | ||
|
|
||
|
|
||
| # Resize to these width and height so that FPS performance increases | ||
| COMPARISON_RESIZE_WIDTH = 320 | ||
| COMPARISON_RESIZE_HEIGHT = 240 | ||
| COMPARISON_RESIZE = (COMPARISON_RESIZE_WIDTH, COMPARISON_RESIZE_HEIGHT) | ||
| COMPARISON_RESIZE_AREA = COMPARISON_RESIZE_WIDTH * COMPARISON_RESIZE_HEIGHT | ||
| MASK_LOWER_BOUND = np.array([0, 0, 0, 1], dtype="uint8") | ||
| MASK_UPPER_BOUND = np.array([MAXBYTE, MAXBYTE, MAXBYTE, MAXBYTE], dtype="uint8") | ||
| START_KEYWORD = "start_auto_splitter" | ||
| RESET_KEYWORD = "reset" | ||
|
|
||
|
|
||
| class ImageType(IntEnum): | ||
| SPLIT = auto() | ||
| RESET = auto() | ||
| START = auto() | ||
|
|
||
|
|
||
| class AutoSplitImage: | ||
| path: str | ||
| filename: str | ||
| flags: int | ||
| loops: int | ||
| image_type: ImageType | ||
| byte_array: MatLike | None = None | ||
| mask: MatLike | None = None | ||
| # This value is internal, check for mask instead | ||
| _has_transparency = False | ||
| # These values should be overriden by some Defaults if None. Use getters instead | ||
| __delay_time: float | None = None | ||
| __comparison_method: int | None = None | ||
| __pause_time: float | None = None | ||
| __similarity_threshold: float | None = None | ||
|
|
||
| def get_delay_time(self, default: "AutoSplit | int"): | ||
| """Get image's delay time or fallback to the default value from spinbox.""" | ||
| if self.__delay_time is not None: | ||
| return self.__delay_time | ||
| if isinstance(default, int): | ||
| return default | ||
| return default.settings_dict["default_delay_time"] | ||
|
|
||
| def __get_comparison_method_index(self, default: "AutoSplit | int"): | ||
| """Get image's comparison or fallback to the default value from combobox.""" | ||
| if self.__comparison_method is not None: | ||
| return self.__comparison_method | ||
| if isinstance(default, int): | ||
| return default | ||
| return default.settings_dict["default_comparison_method"] | ||
|
|
||
| def get_pause_time(self, default: "AutoSplit | float"): | ||
| """Get image's pause time or fallback to the default value from spinbox.""" | ||
| if self.__pause_time is not None: | ||
| return self.__pause_time | ||
| if isinstance(default, (float, int)): | ||
| return default | ||
| return default.settings_dict["default_pause_time"] | ||
|
|
||
| def get_similarity_threshold(self, default: "AutoSplit | float"): | ||
| """Get image's similarity threshold or fallback to the default value from spinbox.""" | ||
| if self.__similarity_threshold is not None: | ||
| return self.__similarity_threshold | ||
| if isinstance(default, (float, int)): | ||
| return default | ||
| return default.settings_dict["default_similarity_threshold"] | ||
|
|
||
| def __init__(self, path: str): | ||
| self.path = path | ||
| self.filename = os.path.split(path)[-1].lower() | ||
| self.flags = flags_from_filename(self.filename) | ||
| self.loops = loop_from_filename(self.filename) | ||
| self.__delay_time = delay_time_from_filename(self.filename) | ||
| self.__comparison_method = comparison_method_from_filename(self.filename) | ||
| self.__pause_time = pause_from_filename(self.filename) | ||
| self.__similarity_threshold = threshold_from_filename(self.filename) | ||
| self.__read_image_bytes(path) | ||
|
|
||
| if START_KEYWORD in self.filename: | ||
| self.image_type = ImageType.START | ||
| elif RESET_KEYWORD in self.filename: | ||
| self.image_type = ImageType.RESET | ||
| else: | ||
| self.image_type = ImageType.SPLIT | ||
|
|
||
| def __read_image_bytes(self, path: str): | ||
| image = cv2.imread(path, cv2.IMREAD_UNCHANGED) | ||
| if not is_valid_image(image): | ||
| self.byte_array = None | ||
| error_messages.image_type(path) | ||
| return | ||
|
|
||
| self._has_transparency = check_if_image_has_transparency(image) | ||
| # If image has transparency, create a mask | ||
| if self._has_transparency: | ||
| # Adaptively determine the target size according to | ||
| # the number of nonzero elements in the alpha channel of the split image. | ||
| # This may result in images bigger than COMPARISON_RESIZE if there's plenty of transparency. | ||
| # Which wouldn't incur any performance loss in methods where masked regions are ignored. | ||
| scale = min(1, sqrt(COMPARISON_RESIZE_AREA / cv2.countNonZero(image[:, :, ColorChannel.Alpha]))) | ||
|
|
||
| image = cv2.resize( | ||
| image, | ||
| dsize=None, | ||
| fx=scale, | ||
| fy=scale, | ||
| interpolation=cv2.INTER_NEAREST, | ||
| ) | ||
|
|
||
| # Mask based on adaptively resized, nearest neighbor interpolated split image | ||
| self.mask = cv2.inRange(image, MASK_LOWER_BOUND, MASK_UPPER_BOUND) | ||
| else: | ||
| image = cv2.resize(image, COMPARISON_RESIZE, interpolation=cv2.INTER_NEAREST) | ||
| # Add Alpha channel if missing | ||
| if image.shape[ImageShape.Channels] == BGR_CHANNEL_COUNT: | ||
| image = cv2.cvtColor(image, cv2.COLOR_BGR2BGRA) | ||
|
|
||
| self.byte_array = image | ||
|
|
||
| def check_flag(self, flag: int): | ||
| return self.flags & flag == flag | ||
|
|
||
| def compare_with_capture( | ||
| self, | ||
| default: "AutoSplit | int", | ||
| capture: MatLike | None, | ||
| ): | ||
| """Compare image with capture using image's comparison method. Falls back to combobox.""" | ||
| if not is_valid_image(self.byte_array) or not is_valid_image(capture): | ||
| return 0.0 | ||
| resized_capture = cv2.resize(capture, self.byte_array.shape[1::-1]) | ||
|
|
||
| return get_comparison_method_by_index( | ||
| self.__get_comparison_method_index(default), | ||
| )( | ||
| self.byte_array, | ||
| resized_capture, | ||
| self.mask, | ||
| ) | ||
|
|
||
|
|
||
| if True: | ||
| from split_parser import ( | ||
| comparison_method_from_filename, | ||
| delay_time_from_filename, | ||
| flags_from_filename, | ||
| loop_from_filename, | ||
| pause_from_filename, | ||
| threshold_from_filename, | ||
| ) |
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