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https://github.com/MaaAssistantArknights/MaaAssistantArknights.git
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https://github.com/MaaAssistantArknights/MaaAssistantArknights/actions/runs/20582634976 [skip changelog]
112 lines
3.7 KiB
Python
112 lines
3.7 KiB
Python
import json
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from pathlib import Path
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import cv2
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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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project_base_path = Path(__file__).parent.parent.parent
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task_paths = {
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"CN": project_base_path / "resource" / "tasks",
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"twxy": project_base_path / "resource/global/txwy/resource/tasks",
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"YoStarEN": project_base_path / "resource/global/YoStarEN/resource/tasks",
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"YoStarJP": project_base_path / "resource/global/YoStarJP/resource/tasks",
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"YoStarKR": project_base_path / "resource/global/YoStarKR/resource/tasks",
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}
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task_files = task_paths["CN"].glob("UiTheme/*.json")
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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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tasks = {}
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for task_file in task_files:
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print("Processing task file:", str(task_file))
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with task_file.open("r", encoding="utf-8") as f:
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task_data = json.load(f)
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crop_doc = task_data.get("crop_doc", {})
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for name, task in task_data.items():
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if name == "crop_doc":
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continue
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if crop_doc:
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task.setdefault("crop_doc", crop_doc)
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tasks[name] = task
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for raw_image in src_path.rglob("*.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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if image is None:
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print(f"Failed to read image: {raw_image}")
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continue
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cur_ratio = image.shape[1] / image.shape[0]
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if cur_ratio >= std_ratio:
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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:
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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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theme_name = str(raw_image.relative_to(src_path).with_suffix(""))
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for i in tasks:
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if "crop_doc" not in tasks[i]:
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continue
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default_temp_name = tasks[f"{i.split('-Entry')[0]}Default"].get(
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"template", ""
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)
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filename = f"{theme_name}/{default_temp_name.split('Default/')[-1]}"
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crop_doc = tasks[i].get("crop_doc", {})
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roi = crop_doc.get("roi")
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if not roi:
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curr = tasks[i]
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while curr:
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if "roi" in curr:
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roi = curr["roi"]
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break
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if "baseTask" in curr and curr["baseTask"] in tasks:
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curr = tasks[curr["baseTask"]]
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else:
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break
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if not roi:
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continue
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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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output_file = dst_path / filename
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output_file.parent.mkdir(parents=True, exist_ok=True)
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print("Saving", output_file)
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cv2.imwrite(str(output_file), cropped)
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print("Finished processing file:", str(raw_image))
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