rpg_public_dronet
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Code for the paper Dronet: Learning to Fly by Driving
1. There are three files in the Udacity dataset link.which one should i use? 2. When I unzipped the ch2_002 file,it contains the following files.  How can I get...
Hi , I cope with this error ` File "F:\time_script\time_stamp_matching3.py", line 67, in match_idx = match_idx[:, 0] IndexError: too many indices for array: array is 1-dimensional, but 2 were indexed...
Hi! Thanks for your amazing works! I have a non-technical issues that I can't download the dataset from Udacity. This repository has been archived by the owner on Nov 26,...
Hi, I am using "time-stamp-matching" to generate “sync_steering .txt” but the error occurs when the program executes to "match_idx = match_idx[:,0]". The error is: File "F:/rpg_public_dronet-master/data_preprocessing/time_stamp_matching.py", line 69, in match_idx...
In my experiment,I notice the value evas is always NaN,and rmse is a value which type is float32, so when execute "evas.tolist(),and rmse.tolist()",the result is : EVA = nan RMSE...
Thank you for your great work. Currently, I am working based on your work. However, when I validated the model by using HMB_2 dataset (since it's quite difficult to download...
Hi, all I have organized my training, testing, evaluation dataset and used time_stamp_matching.py to get the sync_steering.txt file. The following was the file structure: 1. Root_direct:  The collision datasets...
RuntimeWarning: invalid value encountered in true_divide
https://github.com/uzh-rpg/rpg_public_dronet/blob/ac19c54bd6ac5a8fd1d220405ecf6f51af55d1f4/evaluation.py#L154 Do you mean `metrics.recall_score` here?
I want just to see the prediction of a single image using the following code: ` # Model reconstruction from JSON file with open('model_struct.json', 'r') as f: model = model_from_json(f.read())...