Comments (7)
是的,我也遇到了相同的问题。不同的是我使用的是tensorrt8.6.1.6,没有使用8.4.不知道是否存在影响。
参考:
https://blog.csdn.net/qq_42190134/article/details/135365945
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这个有得到解决吗?同样的问题
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[E] [TRT] 3: [runtime.cpp::nvinfer1::Runtime::~Runtime::346] Error Code 3: API Usage Error (Parameter check failed at: runtime.cpp::nvinfer1::Runtime::~Runtime::346, condition: mEngineCounter.use_count() == 1. Destroying a runtime before destroying deserialized engines created by the runtime leads to undefined behavior.
),不知道为什么,出错了还能推理,但性能应该下降了
from tensorrt-alpha.
我有观察到,它在YOLOV8::init中报错了,Parameter check failed在网上有回答说,是因为trt和实际的模型结构不一致导致的,这个希望FeiYull能够解答一下
from tensorrt-alpha.
是的,我也遇到了相同的问题。不同的是我使用的是tensorrt8.6.1.6,没有使用8.4.不知道是否存在影响。
from tensorrt-alpha.
是的,我也遇到了相同的问题。不同的是我使用的是tensorrt8.6.1.6,没有使用8.4.不知道是否存在影响。
参考:
https://blog.csdn.net/qq_42190134/article/details/135365945
你好 ,我用的也是8.6 ,也是这个错误。我看了你说的顺序问题导致的报错,但是我看默认的顺序就是对的啊。请问应该如何修改代码
from tensorrt-alpha.
是的,我也遇到了相同的问题。不同的是我使用的是tensorrt8.6.1.6,没有使用8.4.不知道是否存在影响。
参考:
https://blog.csdn.net/qq_42190134/article/details/135365945你好 ,我用的也是8.6 ,也是这个错误。我看了你说的顺序问题导致的报错,但是我看默认的顺序就是对的啊。请问应该如何修改代码
我的问题是因为在模型转换时出现的问题,如果使用Ultralytics yolo 命令进行转换的engine模型,会在模型头部加一大堆这个模型的信息,前4字节是这个信息的长度跳过去脚好了。大概就是下面这样的情况
with open(weights_path, 'rb') as f, trt.Runtime(logger) as runtime:
meta_len = int.from_bytes(f.read(4), byteorder='little') # read metadata length
metadata = json.loads(f.read(meta_len).decode('utf-8')) # read metadata
if 'description' not in metadata: # Ultralytics YOLOv8 engine
print(" trtexec YOLOv8 engine model")
f.seek(0)
else: # Trtexec yolov8 engine
print(" Ultralytics YOLOv8 engine model")
self.model = runtime.deserialize_cuda_engine(f.read()) # read engine
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