Comments (9)
I have uploaded this 'libmyplugins.so' file, please test again.
环境为Ubuntu18.04 with CUDA 10.2 and cuDNN 8.0.0 TensorRT jetpack自带 PyTorch 1.8.0 and TorchVision 0.9.0 OpenCV-Python 4.5 pycuda 2019.1
你在Jetson板子上运行的吧?libmyplugins.so得重新编译生成
我也遇到同样的问题,非常好的项目,请问如何编译libmyplugins.so
build tensorrtx / yolov5 and generate ***.engine
cd {tensorrtx}/yolov5/
update CLASS_NUM in yololayer.h if your model is trained on custom dataset
mkdir build
cd build
cp {ultralytics}/yolov5/yolov5s.wts {tensorrtx}/yolov5/build
cmake ..
make
没记错的话是这个编译完会有,按流程来就行
from yolov5_deepsort_tensorrt.
I have uploaded this 'libmyplugins.so' file, please test again.
from yolov5_deepsort_tensorrt.
I have uploaded this 'libmyplugins.so' file, please test again.
我也遇到了这个问题,libmyplugins.so已经下载了,路径也没问题,不知道是不是环境哪里有问题呢?
from yolov5_deepsort_tensorrt.
I have uploaded this 'libmyplugins.so' file, please test again.
环境为Ubuntu18.04 with CUDA 10.2 and cuDNN 8.0.0
TensorRT jetpack自带
PyTorch 1.8.0 and TorchVision 0.9.0
OpenCV-Python 4.5
pycuda 2019.1
from yolov5_deepsort_tensorrt.
I have uploaded this 'libmyplugins.so' file, please test again.
环境为Ubuntu18.04 with CUDA 10.2 and cuDNN 8.0.0 TensorRT jetpack自带 PyTorch 1.8.0 and TorchVision 0.9.0 OpenCV-Python 4.5 pycuda 2019.1
你在Jetson板子上运行的吧?libmyplugins.so得重新编译生成
from yolov5_deepsort_tensorrt.
嗯嗯,使用自己生成的文件后跑通了。目前只能用CPU跑,速度在0.5fps,用CUDA的话会报错,单独测试cuda没问题,重装了pytorch还是不行。不知道哪里有问题
Traceback (most recent call last):
File "demo_trt.py", line 60, in
detect(video_path, engine_file_path)
File "demo_trt.py", line 31, in detect
bboxes = detector.detect(img)
File "/home/nvidia/yolov5_deepsort_tensorrt/detector_trt.py", line 120,
in detect
results_trt= self.post_process_new(trt_outputs, origin_h, origin_w)
File "/home/nvidia/yolov5_deepsort_tensorrt/detector_trt.py", line 255,
in post_process_new
pred = torch.Tensor(pred).cuda()
File "/home/nvidia/.local/lib/python3.6/site-packages/torch/cuda/ini
t.py", line 164, in _lazy_init
raise AssertionError("Torch not compiled with CUDA enabled")
AssertionError: Torch not compiled with CUDA enabled
from yolov5_deepsort_tensorrt.
I have uploaded this 'libmyplugins.so' file, please test again.
环境为Ubuntu18.04 with CUDA 10.2 and cuDNN 8.0.0 TensorRT jetpack自带 PyTorch 1.8.0 and TorchVision 0.9.0 OpenCV-Python 4.5 pycuda 2019.1
你在Jetson板子上运行的吧?libmyplugins.so得重新编译生成
问题已解决,jetson有专用的pytorch和torchvision包,需要去nvidia官网安装。目前GPU已跑通,但是NX上的帧率是2fps左右,和您说的6fps有些差距,不知道是为什么,您能提供一些思路吗?
from yolov5_deepsort_tensorrt.
I have uploaded this 'libmyplugins.so' file, please test again.
环境为Ubuntu18.04 with CUDA 10.2 and cuDNN 8.0.0 TensorRT jetpack自带 PyTorch 1.8.0 and TorchVision 0.9.0 OpenCV-Python 4.5 pycuda 2019.1
你在Jetson板子上运行的吧?libmyplugins.so得重新编译生成
问题已解决,jetson有专用的pytorch和torchvision包,需要去nvidia官网安装。目前GPU已跑通,但是NX上的帧率是2fps左右,和您说的6fps有些差距,不知道是为什么,您能提供一些思路吗?
目标的数量一定程度上会影响速度。我过几天有空会更新一版代码,可能会稍微提速一下,具体提升多少还没有空测试过。
from yolov5_deepsort_tensorrt.
I have uploaded this 'libmyplugins.so' file, please test again.
环境为Ubuntu18.04 with CUDA 10.2 and cuDNN 8.0.0 TensorRT jetpack自带 PyTorch 1.8.0 and TorchVision 0.9.0 OpenCV-Python 4.5 pycuda 2019.1
你在Jetson板子上运行的吧?libmyplugins.so得重新编译生成
我也遇到同样的问题,非常好的项目,请问如何编译libmyplugins.so
from yolov5_deepsort_tensorrt.
Related Issues (19)
- ModuleNotFoundError: No module named 'tensorrt' HOT 1
- deepsort加速问题 HOT 2
- 请问有人用pyinstaller 生成可执行程序吗?遇到pycuda问题 HOT 1
- 请问用jetson nano能跑yolov5+deepsort么,帧率能到多少? HOT 1
- Deep SORT error! HOT 5
- Running with Yolov4 HOT 2
- deepsort.engine convert problem HOT 1
- when I convert .pt to .wts,the -w/--weights is needed,how can I do?
- IndexError:invalid index to scalar variable
- [TensorRT] ERROR: coreReadArchive.cpp (38) - Serialization Error in verifyHeader: 0 (Version tag does not match) [TensorRT] ERROR: INVALID_STATE: std::exception [TensorRT] ERROR: INVALID_CONFIG: Deserialize the cuda engine failed. Traceback (most recent call last): File "demo_trt.py", line 15, in <module> import tracker_trt AttributeError: 'NoneType' object has no attribute 'create_execution_context' ------------------------------------------------------------------- PyCUDA ERROR: The context stack was not empty upon module cleanup. ------------------------------------------------------------------- A context was still active when the context stack was being cleaned up. At this point in our execution, CUDA may already have been deinitialized, so there is no way we can finish cleanly. The program will be aborted now. Use Context.pop() to avoid this problem. --------------------------------------------------- HOT 1
- 您好,我的环境是NVIDIA® Jetson Xavier NX,速度很慢,帧率2左右,请问是什么原因? HOT 3
- 关于 faster-rcnn-models
- pycuda._driver.LogicError: cuDeviceGet failed: initialization error HOT 2
- libmyplugins.so在哪? HOT 3
- 作者你好 我想咨询·一下速度问题 HOT 11
- 模型运行时所占的内存怎么看? HOT 1
- 版本问题
- 请问这个移植到板子上的也是有跟踪效果的吗 HOT 3
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from yolov5_deepsort_tensorrt.