Apart from Deepstream where else I can deploy tlt-converted models or .trt engine files

[Morganh]

There are some materials, odds and ends.

PeopleNet. Coverage output is always zero

Hi. I’m trying to inference pruned peoplenet model using tensor rt, but always get zero coverage output. So, i downloaded peoplenet tlt using command from this topic: How to run tlt-converter After that i converted .eltl to engine using next command: ./tlt-converter /home/bronstein/tlt-experiments/resnet34_peoplenet_pruned.etlt -k tlt_encode -o output_cov/Sigmoid,output_bbox/BiasAdd -d 3,544,960 -i nchw -e /home/bronstein/tlt-experiments/engine/peoplenet.engine -m 1 -t fp16 Then i tried t…

Discrepancy between results from tlt-infer and trt engine

I’m doing the inference with yolov3 tensorrt engine converted by tlt-converter, however I found that the inference result from tensorrt engine and that form tlt-infer are different. I think that might due to differences during pre-processing stage. Since I could not get access to the pre-processing part of tlt-infer, I’ve attached below that part for my tensorrt engine: frame = cv2.imread(img_path) reso = (416, 416) ratio_h0, retio_w0 = 416 / frame.shape[0], 416 / frame.shape[1] frame = cv2…

How to run purpose built model Peoplenet on Jetson Nano in my own application?

Hello, I am using Jetson Nano with Jetpack 4.4(recommended in forum) and I want to use Nvidia’s purpose built model Peoplenet in my own application (not deepstream). For clarity, I downloaded the peoplenet’s pruned model from ngc container peoplenet pruned model and used TLT converter downloaded for Jetson and converted the etlt file to TRT engine successfully. I am able to use this generated engine file in deepstream-app, but I don’t find any references how to use it in my custom application. …

Run TrafficCamNet with TensorRT without deepstream

We are trying to run TrafficCamNet pruned model with tensorrt without deepstream. First, I used tlt-converter command adapted from here to generate a TensorRT engine tlt-converter resnet18_trafficcamnet_pruned.etlt -k tlt_encode -c trafficnet_int8.txt -o output_cov/Sigmoid,output_bbox/BiasAdd -d 3,544,960 -i nchw -e trafficnet_int8.engine -m 1 -t int8 -b 1 Then, I run the following code import cv2 import pycuda.autoinit # This is needed for initializing CUDA driver impor…

Run PeopleNet with tensorrt

Hello, We are trying to run Peoplenet pruned model with tensorrt 7 without deepstream. Where can we find a good post-processing code for detectnet model? We have tried some post processing functions:

Incorrect Results When Using TensorRT Inference Server With TLT Model

I am using TLT pre-trained model DashCamNet cache file (the weights and config file from DeepStream SDK) for inference using TensorRT. The issue here is the bounding boxes are off from the regions of interest. Here’s the code snippet that I am using for preprocessing and parsing the output: float net_scale_factor = 0.0039215697906911373; cv::cvtColor(frame,frame,CV_BGR2RGB); int kINPUT_C = 3, mHeight = 544, mWidth = 960; uint8_t buffer[kINPUT_C * mHeight * mWidth]; int nCols = mWidth* kINPU…

How to use purpose-built models like Peoplenet for custom-pipeline

Hi all, I want to use peoplenet and i want to train with my own custom-dataset. After training how to use this model for my custom-pipeline. Please suggest me how to achieve this.

TLT for custom dataset and deploy .engine file

Hi all, I have some question about train the resnet18detectnetv2 for custom my own dataset. 1- I need to converted my own dataset to kitti dataset format? If so, I need first resize images and boxes for fixed size like kitti dataset size as offline? 2- for converting the dataset to tfrecord, tlt-tfrecord-converter expected to have 16 fields in labels text files, I should to fill other fields any value like zeros except x,y,w,h and class id? 3- In the detectnet_v2_train_resnet18_kitti.txt, t…

trt engine inference in python without deepstream

How to do inference of trt engine trained using TLTK in python without deepstream? Let’s say I have trained DetectNet_v2 + ResNet50 using TLTK. Thanks

Deploy .engine file in python

I used Transfer Learning Toolkit to train resnet18detectnetv2 for custom dataset. I then used the tlt-converter to convert the .etlt model into an .engine file. I am able to deploy both the .etlt and .engine file in DeepStream and it works. But now I need to deploy the model in python and I am not able to find how to load the .engine model in python.

How to use tlt trained model on Jetson Nano

Hi, I trained an object-detection model in TLT following examples/detectnet_v2 ipynb. Train & prune & inference & export work well and I got .tlt/.etlt file. How to use these files on Jetson Nano without Deepstream? Is there a python solution likes detectnet_console.py in jetson-inference? Thanks.