Comments (2)
@optimal16
we use NVIDIA SDK Manager to install the latest version of Jetson package. The version info: CUDA 10.0, CUDNN 7.5.0, TensorRT 5.1.6, onnx 1.3.0. Make sure that the onnx used for model conversion and tensorrt parsing should be compatible. If the op is not supported by onnx, you should use newer onnx, consequently a newer tensorrt. When using tensorrt and onnx, we also encountered some strange problem before.
from lffd-a-light-and-fast-face-detector-for-edge-devices.
@optimal16
we use NVIDIA SDK Manager to install the latest version of Jetson package. The version info: CUDA 10.0, CUDNN 7.5.0, TensorRT 5.1.6, onnx 1.3.0. Make sure that the onnx used for model conversion and tensorrt parsing should be compatible. If the op is not supported by onnx, you should use newer onnx, consequently a newer tensorrt. When using tensorrt and onnx, we also encountered some strange problem before.
from lffd-a-light-and-fast-face-detector-for-edge-devices.
Related Issues (20)
- 头部侦测问题 HOT 13
- Four point detection HOT 4
- 头部检测问题 HOT 6
- Nan loss while training face detection model on custom dataset HOT 2
- How to run inside Nvidia Deepstream?
- face detection model failed in the CPU environment HOT 3
- Error in face detection code while testing over WIDER_val dataset
- Error in validation over WIDER_val
- Difference on accuracy between your results and my reproduction HOT 4
- LFFD使用给的pytorch模型无法测试出论文的wider结果
- Please update the repo for Vehicle Detection HOT 6
- 人脸检测结果不符合预期
- 请问运行效率fps是在什么数据集上得到的
- Not realtime when run face_detection program on GPU
- Detecting Tiny Faces HOT 3
- face_detect-python-opencv-dnn
- Basketball tracking and Intel Movidius Myriad X support
- Cuda 10.2+TensorRT 7.0.0.1, Inference issue, ValueError: could not broadcast input array from shape (3,4,3) into shape (3,4,1)
- Slowly when run 2 cameras on 1 machine
- AttributeError: module 'mxnet' has no attribute 'module'
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