Comments (6)
a = np.random.rand(1, 8)
b = np.random.rand(1, 8)
cosine_distance = (a @ b.T) / (np.linalg.norm(a) * np.linalg.norm(b))
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我按照你上述的公式:
train_feature=arcface.commit(train_crop,train_face.landmark).get()
test_feature=arcface.commit(test_crop,test_face.landmark).get()
dist = np.dot(train_feature,test_feature.transpose()) / (np.linalg.norm(train_feature) * np.linalg.norm(test_feature))
得出结果却是:
./face/recognize/2ys1.jpg
dist: [[1.0000001]]
dist: [[1.0000001]]
./face/recognize/2ys3.jpg
dist: [[1.0000001]]
dist: [[1.0000001]]
dist: [[1.0000001]]
dist: [[1.0000001]]
dist: [[1.0000001]]
dist: [[1.0000001]]
dist: [[1.0000002]]
dist: [[1.0000001]]
dist: [[1.0000001]]
./face/recognize/2ys5.jpg
dist: [[1.0000001]]
dist: [[1.0000001]]
dist: [[1.0000001]]
./face/recognize/2ys2.jpg
dist: [[1.0000001]]
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提交了arcface案例,请参考:https://github.com/shouxieai/tensorRT_Pro/blob/main/python/test_arcface.py
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@shouxieai AttributeError: 'trtpy.libtrtpyc.FaceBox' object has no attribute 'width'
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重新编译后解决
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@shouxieai arcface在进行特征提取的时候,为什么需要输入人脸关键点呢?retinaface中有一个函数crop_face_and_landmark裁剪的人脸很大,我想自己裁剪人脸,然后输入到arcface中进行特征提取,应该怎么做呢,之所以这样做,是因为发现提取有些同一个
人脸特征相似度相差很大
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Related Issues (20)
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- 编译不过
- 吐槽
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