[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>
This commit is contained in:
Zheng-Bicheng
2023-01-14 20:40:33 +08:00
committed by GitHub
parent f88c662449
commit 1dabfdf3f1
21 changed files with 712 additions and 147 deletions

View File

@@ -3,7 +3,6 @@ import cv2
import numpy as np
# 余弦相似度
def cosine_similarity(a, b):
a = np.array(a)
b = np.array(b)
@@ -56,24 +55,17 @@ def build_option(args):
args = parse_arguments()
# 配置runtime加载模型
runtime_option = build_option(args)
model = fd.vision.faceid.VPL(args.model, runtime_option=runtime_option)
# 加载图片
face0 = cv2.imread(args.face) # 0,1 同一个人
face1 = cv2.imread(args.face_positive)
face2 = cv2.imread(args.face_negative) # 0,2 不同的人
# 设置 l2 normalize
model.postprocessor.l2_normalize = True
# 预测图片检测结果
result0 = model.predict(face0)
result1 = model.predict(face1)
result2 = model.predict(face2)
# 计算余弦相似度
embedding0 = result0.embedding
embedding1 = result1.embedding
embedding2 = result2.embedding
@@ -81,7 +73,6 @@ embedding2 = result2.embedding
cosine01 = cosine_similarity(embedding0, embedding1)
cosine02 = cosine_similarity(embedding0, embedding2)
# 打印结果
print(result0, end="")
print(result1, end="")
print(result2, end="")