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简介

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图像清晰度计算处理器

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功能描述

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算子参数

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输入

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输入含义
image包含输入图像的数组，支持URL/base64/二进制格式
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输出

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输出含义
image_sharpness包含清晰度计算结果的浮点数组
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参数

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参数名称类型默认值描述
image_src_typestr\"image_url\"输入图像的格式类型，支持：image_url：url地址image_base64：base64编码image_binary：二进制流默认值: \"image_url\"
methodstr\"laplacian\"清晰度计算方法，支持：laplacian(拉普拉斯方差)tenengrad(Tenengrad梯度)brenner(Brenner梯度)fft_highfreq(FFT高频能量)默认为 laplacian。
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调用示例

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1from __future__ import annotations\n2\n3import os\n4import daft\n5from daft import col\n6\n7from daft.aihc.common.udf import aihc_udf\n8from daft.aihc.functions.image.image_sharpness import ImageSharpness\n9\n10if __name__ == "__main__":\n11    if os.getenv("DAFT_RUNNER", "native") == "ray":\n12        import ray\n13        ray.init(dashboard_host="0.0.0.0", ignore_reinit_error=True)\n14        daft.set_runner_ray()\n15    daft.set_execution_config(actor_udf_ready_timeout=6000, min_cpu_per_task=0)\n16\n17   samples = {\n18        "image": [\n19            "file:///local/sample_1.jpg",\n20            "file:///mnt/pfs/sample_2.jpg",\n21            "file:///mnt/bos/sample_3.jpg",\n22        ]\n23    }\n24     \n25    image_src_type = "image_url"\n26    method = "laplacian"\n27\n28    ds = daft.from_pydict(samples)\n29    ds = ds.with_column(\n30        "image_sharpness",\n31        aihc_udf(\n32            ImageSharpness,\n33            construct_args={\n34                "image_src_type": image_src_type,\n35                "method": method,\n36            },\n37            batch_size=1,\n38        )(col("image")),\n39    )\n40\n41    ds.show()
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