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Update README.md,windows.md and demo.cpp

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Small fixes in DeformableConvRT.cpp
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perseusdg
2021-11-09 13:37:26 +05:30
parent d2d44e9e92
commit 744396fb0e
6 changed files with 61 additions and 38 deletions
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docs/demo.md
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@@ -26,27 +26,35 @@ rm yolo4_fp32.rt # be sure to delete(or move) old tensorRT files
```
If you get problems in the creation, try to check the error activating the debug of TensorRT in this way:
```
cmake .. -DDEBUG=True
cmake .. -DCMAKE_BUILD_TYPE=Debug -DDEBUG=True
make
```
Once you have successfully created your rt file, run the demo:
Once you have successfully created your rt file, run the demo(yolo) :
```
./demo yolo4_fp32.rt ../demo/yolo_test.mp4 y
./demo yolo4_fp32.rt ../demo/yolo_test.mp4 y 80 ../tests/darknet/cfg/yolo4.cfg ../tests/darknet/names/cococ.names
```
To run demo for mobilenet and centernet for the created rt file :
```
./demo mobilenetv2ssd_fp32.rt m 20
```
In general the demo program takes 7 parameters:
```
./demo <network-rt-file> <path-to-video> <kind-of-network> <number-of-classes> <n-batches> <show-flag> <conf-thresh>
./demo <network-rt-file> <path-to-video> <kind-of-network> <number-of-classes> <cfg-path> <name-path> <n-batches> <show-flag> <conf-thresh>
```
where
* ```<network-rt-file>``` is the rt file generated by a test
* ```<<path-to-video>``` is the path to a video file or a camera input
* ```<kind-of-network>``` is the type of network. Thee types are currently supported: ```y``` (YOLO family), ```c``` (CenterNet family) and ```m``` (MobileNet-SSD family)
* ```<number-of-classes>```is the number of classes the network is trained on
* ```<n-batches>``` number of batches to use in inference (N.B. you should first export TKDNN_BATCHSIZE to the required n_batches and create again the rt file for the network).
* ```<show-flag>``` if set to 0 the demo will not show the visualization but save the video into result.mp4 (if n-batches ==1)
* ```<conf-thresh>``` confidence threshold for the detector. Only bounding boxes with threshold greater than conf-thresh will be displayed.
* ```<network-rt-file>``` is the rt file generated by a test
* ```<<path-to-video>``` is the path to a video file or a camera input
* ```<kind-of-network>``` is the type of network. Thee types are currently supported: ```y``` (YOLO family), ```c``` (CenterNet family) and ```m``` (MobileNet-SSD family)
* ```<number-of-classes>```is the number of classes the network is trained on
* ```<cfg-path> ```is the relative path to the config file (only for darknet based networks) used to train the network
* ```<name-path>```is the relative path to the names file (only for darknet based networks) used to train the network
* ```<n-batches>``` number of batches to use in inference (N.B. you should first export TKDNN_BATCHSIZE to the required n_batches and create again the rt file for the network).
* ```<show-flag>``` if set to 0 the demo will not show the visualization but save the video into result.mp4 (if n-batches ==1)
* ```<conf-thresh>``` confidence threshold for the detector. Only bounding boxes with threshold greater than conf-thresh will be displayed.
N.B. By default it is used FP32 inference