Closed krish240574 closed 4 years ago
in your workspace there is a folder called tmp_datasets. Here is the .npz file. This file contains your renderings and masks.
What I did was to create a new script to generate data for the retinanet training using the .npz file of already rendered images: random background images, random scaling, location, noise etc etc, and automatically annotate boundary boxes etc in a csv file that retinanet can read directly.
Step 1+2: You can do it as flugenheimer proposed or you can run the generate_syn_det_train.py to create training data for RetinaNet. In both cases you need to transform the labels into the .csv format needed by the RetinaNet repository. Step 3: Yes, use the same ply file here.
Hello, Thank you very much for the great work, much appreciated. I am trying to render and subsequently train the AAE using my own set of models. These are models of various cars. I intend to use the whole pipeline, object detection and pose estimation too.
Could you please list the steps I must follow, to achieve the same? The documentation in the Readme seems incomplete.
Edit: Here is what I have understood, please do correct me if I'm wrong : Step 1: Generate data for the detector.
Step 3: Train the AAE In the README, it mentions "Insert the paths to your 3D model and background images" - does it mean I use the same .ply used in the generate_syn_det_train.py, along with VOC images here?
Thank you very much, Kumar