print('--> Building model') ret = rknn.build(do_quantization = False) if ret != 0: print('Build model failed!') exit(ret) print('done') # 导出模型 # export_path:导出模型文件(.rknn后缀)的路径 # 返回值:0(成功)、-1(失败) print('--> Export RKNN model') ret = r...
--> Building model Build model failed! E build: Catch exception when building RKNN model! E build: Traceback (most recent call last): E build: File "rknn/api/rknn_base.py", line 1979, in rknn.api.rknn_base.RKNNBase.build E build: File "rknn/api/graph_optimizer.py", line 1365, i...
E File "rknn/api/rknn_runtime.py", line 356, in rknn.api.rknn_runtime.RKNNRuntime.build_graph E Exception: RKNN init failed. error code: RKNN_ERR_MODEL_INVALID Init runtime environment failed大佬大佬,我自己训练的darknet模型,量化时有warning,有rknn模型输出,但Init runtime environment failed,...
W rknn-toolkit version: 1.7.5 D Using CPPUTILS: True I Start importing tflite...I Model: ...
ret = rknn.load_onnx(model=ONNX_MODEL, outputs=['output1', 'output2', 'output3']) if ret != 0: print('Load model failed!') exit(ret) print('done') # Build model print('--> Building model') ret = rknn.build(do_quantization=QUANTIZE_ON, dataset=DATASET, rknn_batch_size=1)...
ret = rknn.load_onnx(model=ONNX_MODEL,outputs=['output', '327', '328'])# 这里一定要根据onnx模型修改 if ret != 0: print('Load onnx model failed!') exit(ret) print('done') # Build model print('--> Building model') ret = rknn.build(do_quantization=True, dataset='./dataset....
I am running rknn toolkit for building a model.rknn for running on RK3566. After rknn.load_onnx() successfully, when run rknn.build(), the following error message occur: --> Loading model: ./rknn_models/model_3566.onnx done --> Building ...
=0:print('Load model failed!')exit(ret)print('done')# Build model#hybrid_quantization_step1用于生成临时模型文件,数据文件及量化配置参数文件#其中proposal:产生混合量化的配置建议值。#proposal_dataset_size:proposal 使用的 dataset 的张数。默认值为1。print('--> hybrid_quantization_step1')# ret = ...
1. 检查ONNX模型中的输入和输出形状是否正确。确保它们与RKNN模型中的定义相匹配。2. 在RKNN模型中重新...
= 0: print('Load mobilenet_v1 failed!') exit(ret) print('done') # Build model print('--> Building model') ret = rknn.build(do_quantization=True, dataset='./dataset.txt') if ret != 0: print('Build mobilenet_v1 failed!') exit(ret) print('done') 13 # Export rknn model ...