Toybrick

标题: 调用librknn_api接口移植pytorch模型 [打印本页]

作者: Leonod 时间: 2020-12-3 15:37
标题: 调用librknn_api接口移植pytorch模型
楼主调用以下脚本：______________________________

import numpy as np
import cv2
from rknn.api import RKNN
import torchvision.models as models
import torch

def export_pytorch_model():
net = models.resnet18(pretrained=True)
net.eval()
trace_model = torch.jit.trace(net, torch.Tensor(1,3,224,224))
trace_model.save('./resnet18.pt')

def show_outputs(output):
output_sorted = sorted(output, reverse=True)
top5_str = '\n-----TOP 5-----\n'
for i in range(5):
      value = output_sorted[i]
      index = np.where(output == value)
      for j in range(len(index)):
         if (i + j) >= 5:
            break
         if value > 0:
            topi = '{}: {}\n'.format(index[j], value)
         else:
            topi = '-1: 0.0\n'
         top5_str += topi
print(top5_str)

def show_perfs(perfs):
perfs = 'perfs: {}\n'.format(perfs)
print(perfs)

def softmax(x):
return np.exp(x)/sum(np.exp(x))

if __name__ == '__main__':

export_pytorch_model()
model = './resnet18.pt'
input_size_list = [[3,224,224]]
rknn = RKNN()
print('--> config model')
rknn.config(channel_mean_value='123.675 116.28 103.53 58.395', reorder_channel='0 1 2')
print('done')
print('--> Loading model')
ret = rknn.load_pytorch(model=model, input_size_list=input_size_list)
if ret != 0:
      print('Load pytorch model failed!')
      exit(ret)
print('done')
print('--> Building model')
ret = rknn.build(do_quantization=True, dataset='./dataset.txt')
if ret != 0:
      print('Build pytorch failed!')
      exit(ret)
print('done')
print('--> Export RKNN model')
ret = rknn.export_rknn('./resnet_18.rknn')
if ret != 0:
      print('Export resnet_18.rknn failed!')
      exit(ret)
print('done')

ret = rknn.load_rknn('./resnet_18.rknn')

# Set inputs
img = cv2.imread('./space_shuttle_224.jpg')
img = cv2.cvtColor(img, cv2.COLOR_BGR2RGB)

# init runtime environment
print('--> Init runtime environment')
ret = rknn.init_runtime()
if ret != 0:
      print('Init runtime environment failed')
      exit(ret)
print('done')
print('--> Running model')
outputs = rknn.inference(inputs=[img])
show_outputs(softmax(np.array(outputs[0][0])))
print('done')
rknn.release()

————————————————————————————————————————————
可以将pytorch的模型转换为rknn的模型，并且能够输出推断结果。

现在楼主想在调用rknn提供的c语言接口(库为librknn_api.so),实现加载模型(pytorch模型转rknn模型的模型)，推断输出目标的类型，坐标位置，置信度信息。请问有相关的示例代码吗？

欢迎光临 Toybrick (https://t.rock-chips.com/)