import io
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import numpy as np
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from PIL import Image
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def load_image_any(source):
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"""统一加载为 Pillow Image 对象，并返回原类型标记"""
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if isinstance(source, Image.Image):
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return source.convert("RGBA"), "image"
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if isinstance(source, np.ndarray):
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return Image.fromarray(source).convert("RGBA"), "ndarray"
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if isinstance(source, bytes):
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return Image.open(io.BytesIO(source)).convert("RGBA"), "bytes"
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raise ValueError("不支持的图片输入类型")
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def resize_and_crop_center_any(source, target_w, target_h):
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img, src_type = load_image_any(source)
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if img is None:
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return None
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src_w, src_h = img.size
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target_ratio = target_w / target_h
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src_ratio = src_w / src_h
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# 计算缩放比例（保证一边刚好，另一边多出来）
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if src_ratio > target_ratio:
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scale = target_h / src_h # 按高度匹配
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else:
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scale = target_w / src_w # 按宽度匹配
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new_w = int(src_w * scale)
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new_h = int(src_h * scale)
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img_resized = img.resize((new_w, new_h), Image.LANCZOS)
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# 居中裁剪
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left = max((new_w - target_w) / 2, 0)
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top = max((new_h - target_h) / 2, 0)
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right = left + target_w
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bottom = top + target_h
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img_cropped = img_resized.crop((left, top, right, bottom))
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# 返回与原输入一致的类型
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if src_type == "image":
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return img_cropped
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elif src_type == "bytes":
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buf = io.BytesIO()
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img_cropped.save(buf, format="PNG")
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return buf.getvalue()
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elif src_type == "ndarray":
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return np.array(img_cropped)
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else:
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return img_cropped # 兜底，返回 Pillow Image
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