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Update readme.

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Signed-off-by: Davide Sapienza <sapienza.dav@gmail.com>
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Davide Sapienza
2020-12-07 18:56:07 +01:00
parent 48ecebe6dd
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@@ -169,6 +169,16 @@ cd pytorch-ssd
conda env create -f env_mobv2ssd.yml conda env create -f env_mobv2ssd.yml
python run_ssd_live_demo.py mb2-ssd-lite <pth-model-fil> <labels-file> python run_ssd_live_demo.py mb2-ssd-lite <pth-model-fil> <labels-file>
``` ```
### 5)Export weights for CenterTrack
To get the weights needed to run CenterTrack tests use [this](https://github.com/sapienzadavide/CenterTrack.git) fork of the original CenterTrack.
```
git clone https://github.com/sapienzadavide/CenterTrack.git
```
* follow the instruction in the README.md and INSTALL.md
```
python demo.py tracking,ddd --load_model ../models/nuScenes_3Dtracking.pth --dataset nuscenes --pre_hm --track_thresh 0.1 --demo /path/to/image/or/folder/or/video/or/webcam --test_focal_length 633 --exp_wo --exp_wo_dim 512 --input_h 512 --input_w 512
```
## Darknet Parser ## Darknet Parser
tkDNN implement and easy parser for darknet cfg files, a network can be converted with *tk::dnn::darknetParser*: tkDNN implement and easy parser for darknet cfg files, a network can be converted with *tk::dnn::darknetParser*:
@@ -246,6 +256,15 @@ The demo3D program takes the same parameters of the demo program:
./demo <network-rt-file> <path-to-video> <kind-of-network> <number-of-classes> ./demo <network-rt-file> <path-to-video> <kind-of-network> <number-of-classes>
``` ```
#### Run the 3D OD-tracking demo
To run the 3D object detection & tracking demo follow these steps (example with CenterTrack based on DLA34):
```
rm dla34_cnet3d_track_fp32.rt # be sure to delete(or move) old tensorRT files
./test_dla34_cnet3d_track # run the yolo test (is slow)
./demo3D dla34_cnet3d_track_fp32.rt ../demo/yolo_test.mp4 t
```
### FP16 inference ### FP16 inference
To run the an object detection demo with FP16 inference follow these steps (example with yolov3): To run the an object detection demo with FP16 inference follow these steps (example with yolov3):