I want to retrain a Pre-trained object detection model used in deepstream-image-meta-test code with my own custom dataset (images).
My objective is to increase the accuracy of my model by training it on the custom set of images.
As per my observation, the deepstream-image-meta-test.c code uses the model built on caffe framework.
I wish to retrain the same model used in that code to train with my custom dataset.
Is there a way to do so?
Please guide me the required steps to perform the model training on my custom dataset.
TensorRT Version: 7.1.3-1+cuda10.2
GPU Type: Nvidia Tegra X1
Nvidia Driver Version:
CUDA Version: 10.2
Operating System + Version: ubuntu 18.04 LTS 64 bit
Python Version (if applicable): 3.6.9
TensorFlow Version (if applicable):
PyTorch Version (if applicable):
Baremetal or Container (if container which image + tag):
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