Update README and add print in demo

Signed-off-by: Micaela Verucchi <micaelaverucchi@gmail.com>

README.md

@@ -17,9 +17,15 @@ If you use tkDNN in your research, please cite the [following paper](https://iee
 }
 ```
 
-### What's new (November 2021)
-- [x] Support to sematic segmentation on cuda 11+ [README](docs/README_seg.md)
-- [x] Support to TensorRT8 
+### What's new
+#### 20 July 2021
+- [x] Support to sematic segmentation [README](docs/README_seg.md)
+- [x] Support 2D/3D Object Detection and Tracking [README](docs/README_2d3dtracking.md)
+#### 24 November 2021
+- [x] Support to sematic segmentation on cuda 11
+- [x] Support to TensorRT8. 
+
+TensorRT8 (and therefore Jetpack 4.6) is currently supported only on the branch tensort8 due to [performance issue with TensorRT8](https://docs.nvidia.com/deeplearning/tensorrt/release-notes/tensorrt-8.html)). We will merge it to the master as soon as those issues are fixed (probably in future minor releases).
 
 ## FPS Results
 Inference FPS of yolov4 with tkDNN, average of 1200 images with the same dimension as the input size, on 
@@ -81,7 +87,7 @@ Results for COCO val 2017 (5k images), on RTX 2080Ti, with conf threshold=0.001
 
 ## Dependencies
 This branch works on every NVIDIA GPU that supports the following (latest tested) dependencies:
-* CUDA 11.3 (or >= 10.2) [the segmentation only works with CUDA 10 for now]
+* CUDA 11.3 (or >= 10.2) 
 * cuDNN 8.2.1 (or >= 8.0.4)
 * TensorRT 8.0.3 (or >=7.2)
 * OpenCV 4.5.4 (or >=4)

demo/demo/demo.cpp

@@ -62,12 +62,14 @@ int main(int argc, char *argv[]) {
     bool show           = YAMLgetConf<bool>(conf, "show", true);
     bool save           = YAMLgetConf<bool>(conf, "save", false);
 
-
-
-
-
-
-
+    std::cout   <<"Net settings - net: "<< net
+                <<", ntype: "<< ntype
+                <<", n_classes: "<< n_classes
+                <<", n_batch: "<< n_batch
+                <<", conf_thresh: "<< conf_thresh<<"\n"; 
+    std::cout   <<"Demo settings - input: "<< input
+                <<", show: "<< show
+                <<", save: "<< save<<"\n\n"; 
 
     tk::dnn::Yolo3Detection yolo;
     tk::dnn::CenternetDetection cnet;