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96 lines
3.5 KiB
Python
96 lines
3.5 KiB
Python
import cv2
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import json
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from pathlib import Path
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"""
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This is a tool for cropping one image into several images based on current roi.
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Use this tool when a raw image contains many templates.
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For example, when adding a new homepage theme.
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Put one picture in ./src and add the template's tasks to 'task_list',
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This tools will try to read roi (if not 'crop_doc') from tasks in tasks.json and then crop the image.
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"""
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std_width: int = 1280
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std_height: int = 720
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std_ratio = std_width / std_height
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task_paths = {
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"CN": Path(__file__).parent.parent.parent / "resource" / "tasks.json",
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"twxy": Path(__file__).parent.parent.parent / "resource" / "global" / "txwy" / "resource" / "tasks.json",
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"YoStarEN": Path(__file__).parent.parent.parent / "resource" / "global" / "YoStarEN" / "resource" / "tasks.json",
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"YoStarJP": Path(__file__).parent.parent.parent / "resource" / "global" / "YoStarJP" / "resource" / "tasks.json",
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"YoStarKR": Path(__file__).parent.parent.parent / "resource" / "global" / "YoStarKR" / "resource" / "tasks.json"
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}
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# Change this to your client
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task_file = task_paths["CN"]
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# Add the tasks you want to get its image
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# task_list = []
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# You should get these names from tasks.json
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#
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# For example, when adding a new homepage theme:
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task_list = [
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"Award", # Task.png
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"GachaEnter", # GachaEnter.png
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"Home", # Terminal.png
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"Infrast", # EnterInfrast.png
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"OperBoxEnter", # OperBoxEnter.png
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"Recruit", # Recruit.png
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"Visit", # Friends.png
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"DepotEnter", # DepotEnter.png
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"Mall", # Mall.png
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]
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src_path = Path(__file__).parent / "src"
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dst_path = Path(__file__).parent / "dst"
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if __name__ == "__main__":
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with task_file.open("r", encoding="utf-8") as f:
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tasks = json.load(f)
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for raw_image in src_path.glob("*.png"):
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print("Processing file:", str(raw_image))
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image = cv2.imread(str(raw_image))
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cur_ratio = image.shape[1] / image.shape[0]
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if cur_ratio >= std_ratio: # 说明是宽屏或默认16:9，按照高度计算缩放
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dsize_width: int = (int)(cur_ratio * std_height)
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dsize_height: int = std_height
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else: # 否则可能是偏正方形的屏幕，按宽度计算
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dsize_width: int = std_width
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dsize_height: int = std_width / cur_ratio
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dsize = (dsize_width, dsize_height)
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image = cv2.resize(image, dsize, interpolation=cv2.INTER_AREA)
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for i in task_list:
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if "template" not in tasks[i]:
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filename = i + ".png"
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elif isinstance(tasks[i]["template"], str):
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filename = tasks[i]["template"]
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elif isinstance(tasks[i]["template"], list):
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# this is for multi-temSplate:
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filename = (
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tasks[i]["template"][0].split(".")[0] + raw_image.stem + ".png"
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)
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crop_doc = tasks[i].get("crop_doc", {})
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roi = crop_doc.get("roi", tasks[i]["roi"])
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mask = crop_doc.get("mask", [])
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cropped = image[roi[1] : roi[1] + roi[3], roi[0] : roi[0] + roi[2]]
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if len(mask) > 0:
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cv2.rectangle(
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cropped,
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(mask[0], mask[1]),
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(mask[0] + mask[2], mask[1] + mask[3]),
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(0, 0, 0),
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-1,
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)
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print("Saving", dst_path / filename)
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cv2.imwrite(str(dst_path / filename), cropped)
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print("Finished processing file:", str(raw_image))
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