The completed application runs any [Model Zoo](https://github.com/tensorflow/models/blob/master/research/object_detection/g3doc/detection_model_zoo.mdTensorflow) style object detector in Tensorflow mode (default) and an Inception V2 SSD detector converted from Tensorflow graph to UFF format recognized by TensorRT in TensorRT mode (-t).
## Setting up the environment
Read these [series of posts](https://viralfsharp.com/2019/03/25/supercharging-object-detection-in-video-from-glacial-to-lightning-speed/)
## Building the app
* Clone the [repo](https://github.com/fierval/fast_od).
...
...
@@ -37,4 +41,4 @@ Examples are in `run_*.sh` files in the sources directory. Worth mentioning:
```
## Slowdown due to UX
The application uses a bare-bones OpenCV UI for visual feedback (`imshow`) and that causes a significant perf hit, so to measure actual performance we run with `-d=0` which suppresses the UI.
\ No newline at end of file
The application uses a bare-bones OpenCV UI for visual feedback (`imshow`) and that causes a significant perf hit, so to measure actual performance we run with `-d=0` which suppresses the UI.
