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[Model] Support Insightface model inferenceing on RKNPU (#1113)
* 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * 更新交叉编译 * Update issues.md * Update fastdeploy_init.sh * 更新交叉编译 * 更新insightface系列模型的rknpu2支持 * 更新insightface系列模型的rknpu2支持 * 更新说明文档 * 更新insightface * 尝试解决pybind问题 Co-authored-by: Jason <928090362@qq.com> Co-authored-by: Jason <jiangjiajun@baidu.com>
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@@ -3,7 +3,6 @@ import cv2
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import numpy as np
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# 余弦相似度
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def cosine_similarity(a, b):
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a = np.array(a)
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b = np.array(b)
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@@ -56,24 +55,18 @@ def build_option(args):
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args = parse_arguments()
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# 配置runtime,加载模型
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runtime_option = build_option(args)
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model = fd.vision.faceid.PartialFC(args.model, runtime_option=runtime_option)
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# 加载图片
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face0 = cv2.imread(args.face) # 0,1 同一个人
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face0 = cv2.imread(args.face)
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face1 = cv2.imread(args.face_positive)
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face2 = cv2.imread(args.face_negative) # 0,2 不同的人
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face2 = cv2.imread(args.face_negative)
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# 设置 l2 normalize
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model.postprocessor.l2_normalize = True
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# 预测图片检测结果
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result0 = model.predict(face0)
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result1 = model.predict(face1)
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result2 = model.predict(face2)
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# 计算余弦相似度
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embedding0 = result0.embedding
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embedding1 = result1.embedding
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embedding2 = result2.embedding
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@@ -81,7 +74,6 @@ embedding2 = result2.embedding
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cosine01 = cosine_similarity(embedding0, embedding1)
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cosine02 = cosine_similarity(embedding0, embedding2)
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# 打印结果
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print(result0, end="")
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print(result1, end="")
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print(result2, end="")
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