ttanzhiqiang / onnx_tensorrt_project Goto Github PK

I run the retinafece, it show this, so it is not right

my windows eviroment is:
cuda 11.0
vs2019
how to run?
when i run, it tip me:
can not find the nvrtc64_111_0.dll

which third_model should i to recompile them?

reading calib cache: E:\comm_Item\Item_done\onnx_tensorrt_pro\onnx_tensorrt_project-main\model\pytorch_onnx_tensorrt_yolov5\yolov5s.table
TensorRT was linked against cuDNN 8.1.0 but loaded cuDNN 8.0.2
Detected 1 inputs and 7 output network tensors.
TensorRT was linked against cuDNN 8.1.0 but loaded cuDNN 8.0.2
TensorRT was linked against cuDNN 8.1.0 but loaded cuDNN 8.0.2
Starting Calibration.
dog.jpg 0
Calibrated batch 0 in 1.35348 seconds.
person.jpg 1
Calibrated batch 1 in 1.3612 seconds.
Post Processing Calibration data in 0.0005131 seconds.
Calibration completed in 20.8498 seconds.
reading calib cache: E:\comm_Item\Item_done\onnx_tensorrt_pro\onnx_tensorrt_project-main\model\pytorch_onnx_tensorrt_yolov5\yolov5s.table
Writing Calibration Cache for calibrator: TRT-7203-MinMaxCalibration
writing calib cache: E:\comm_Item\Item_done\onnx_tensorrt_pro\onnx_tensorrt_project-main\model\pytorch_onnx_tensorrt_yolov5\yolov5s.table size: 4711
TensorRT was linked against cuDNN 8.1.0 but loaded cuDNN 8.0.2
C:\source\rtSafe\cuda\cudaConvolutionRunner.cpp (483) - Cudnn Error in nvinfer1::rt::cuda::CudnnConvolutionRunner::executeConv: 8 (CUDNN_STATUS_EXECUTION_FAILED)
C:\source\rtSafe\cuda\cudaConvolutionRunner.cpp (483) - Cudnn Error in nvinfer1::rt::cuda::CudnnConvolutionRunner::executeConv: 8 (CUDNN_STATUS_EXECUTION_FAILED)
[2021-08-08 11:28:54.729] [info] serialize engine to E:\comm_Item\Item_done\onnx_tensorrt_pro\onnx_tensorrt_project-main\model\pytorch_onnx_tensorrt_yolov5\yolov5s_fp32_batch_1.engine
[2021-08-08 11:28:54.730] [error] engine is empty, save engine failed
[2021-08-08 11:28:54.731] [info] create execute context and malloc device memory...
[2021-08-08 11:28:54.731] [info] init engine...

您好，感谢您的开源工作，如题我现在已经转换得到onnx了，但是另一个文件yolov5x_fp32_batch_1.engine不知道怎么生成或者得到的，新手，希望大神能指导一下，谢谢

Hi, I tried to transfer yolo3-spp pt file to onnx, and here is the error:

Traceback (most recent call last):
File "Libtorch_yolo_to_onnx.py", line 779, in
main()
File "Libtorch_yolo_to_onnx.py", line 771, in main
model_def = builder.build_onnx_graph(
File "Libtorch_yolo_to_onnx.py", line 353, in build_onnx_graph
major_node_specs = self._make_onnx_node(layer_name, layer_dict)
File "Libtorch_yolo_to_onnx.py", line 426, in _make_onnx_node
node_creators[layer_type](layer_name, layer_dict)
File "Libtorch_yolo_to_onnx.py", line 729, in _make_yolo_node
down_stride = int(layer_dict['down_stride'])
KeyError: 'down_stride'

many thanks!

-Scott

Hi,

I trained a model with the public dataset but the result is strange. Could you please some tips for training.

Thanks.

I have one class and I set the classes param to 2

unet_model = Unet(encoder_name="resnet50", encoder_weights="imagenet", decoder_channels=(256, 128, 64, 32, 16),
                  in_channels=3, classes=2)

--width: 512
--height: 512
--epoch: 30
--batchsize: 2

dataset sample:
900 images

Result:

如题，我看源码是支持int8的，想尝试一下，但是不知道步骤，大神有具体的步骤吗？我尝试时老是失败，是需要先生成int8的模型吗？还是怎么操作呢？

is there a demo to convert libtorch nn::Module trained model to onnx model? python can convert it by torch.onnx.export, but in libtorch c++ can not export it. can you help me to solve this isssue?

如题，不知道作者是否遇到过，训练完成的yolov5x模型，在python版本正确率为98%，但是转换为tensorrt后经过测试，正确率只有90%左右，其中模型转换过程log如下：
[09/27/2021-11:27:04] [I] Host Latency
[09/27/2021-11:27:04] [I] min: 11.3848 ms (end to end 21.3677 ms)
[09/27/2021-11:27:04] [I] max: 13.1256 ms (end to end 24.1753 ms)
[09/27/2021-11:27:04] [I] mean: 11.67 ms (end to end 21.9034 ms)
[09/27/2021-11:27:04] [I] median: 11.5836 ms (end to end 21.7285 ms)
[09/27/2021-11:27:04] [I] percentile: 12.5283 ms at 99% (end to end 23.6667 ms at 99%)
[09/27/2021-11:27:04] [I] throughput: 0 qps
[09/27/2021-11:27:04] [I] walltime: 3.03151 s
[09/27/2021-11:27:04] [I] Enqueue Time
[09/27/2021-11:27:04] [I] min: 1.04535 ms
[09/27/2021-11:27:04] [I] max: 4.6637 ms
[09/27/2021-11:27:04] [I] median: 1.61969 ms
[09/27/2021-11:27:04] [I] GPU Compute
[09/27/2021-11:27:04] [I] min: 10.8311 ms
[09/27/2021-11:27:04] [I] max: 12.5458 ms
[09/27/2021-11:27:04] [I] mean: 11.0955 ms
[09/27/2021-11:27:04] [I] median: 11.0142 ms
[09/27/2021-11:27:04] [I] percentile: 11.9821 ms at 99%
[09/27/2021-11:27:04] [I] total compute time: 3.01798 s
&&&& PASSED TensorRT.trtexec # trtexec.exe --onnx=best.onnx --saveEngine=best.engine --fp16

I do not find the yolox?

Hello,

Thanks for the great work!!!

Can one use ubuntu? or must it be on Windows?

If yes, please can you provide more information for non windows users.

Thanks once again

great work! how fast of centernet tensorrt model?

如题，yolov5_detector.cpp在推理阶段时如果输入的batch是多个的话（即大于1）

那么会报以下错误：

请问有可能是什么原因导致的呢？

weights 转onnx c++ 例子有吗

如题，我按照您的配置成功运行起来了unet.cpp，图像指定大小是512*512，显卡型号3060，mode是2（INT8）但是检测下来检测速度是在77ms左右，与您在此项目中的Benchmark中提到的16ms相差甚远，显存占用也有1.2G，请问根据您的经验来看我还有哪些地方没设置对？

(https://github.com/ttanzhiqiang/onnx_tensorrt_project/tree/main/src/classify)/classify.cpp 143行开始

每个image都是同一个auto& tensor : m_OutputTensors，那每张图的结果都是一样了？？