junctionhilt.blogg.se - Hotswitch between xorg and wayland

#Hotswitch between xorg and wayland install
#Hotswitch between xorg and wayland software
#Hotswitch between xorg and wayland code

The schematic of the Sense Hat can be found here.

#Hotswitch between xorg and wayland code

Via glob the code makes contact with /dev/i2c* and /sys/class/graphics/fb*.Looked at the code of sense hat, but it seems that the device is controlled via glob (for the led-frame) and RTIMU (for the IMU and the three other sensors).For the Raspberry the GND is on pin 6, while for 96boards the GND is on pin 1 and 2.Compared the 40-pins Raspberry GPIO configuration vs the 40-pins 96boards low speed extension.Followed the Installation instructions (now on robolabws7), but ~/AutonomousDriving/CARLA/PythonAPI/*/*.py also contains no main.py.Tried to reproduce Thomas work on Town02, with the command python3 main.py-benchmark -synchronous -fps 25 -weights weights_Xception/ -configtest_config.json Town02, but Thomas github doesn't contain main.py.Thomas was training the networks over 50 epochs, with train loss below 0.01 (see Table 6 on page 45).Killed the session from an other terminal with tmux kill-session -t town01. Script hangs on terminate called without an active exception. After 10 epochs val_loss improved from 1.58471 to 1.58232. Seems that it only trained one epoch (as requested). The training is ready in a minute (which I doubt).Yet, the model chosen here is Xception, so removing EfficientNetB7 from the import in train.py solves this issue. As indicated in the Readme, EfficientNet is only included in the Tensoflow-GPU version 2.3 and higher.it failed on the import of 'EfficientNetB7'. Yet, with from import ResNet50, ResNet101V2. Started training with command train.py -N 1000 -split 0.8 -model Xception -epochs 1 -batchsize 32 -scale 20 -info TEST_RUN1 ~/carla/dataset/20200621/.This directory contains all images used for training the steeringmodels. ColorConverter is also part of matplotlib, but that doesn't help.Problems seems to be that my python3 is v3.6.9, while the egg file is for v3.5.This installed three packages, but not ColorConverter.

#Hotswitch between xorg and wayland install

Without root-permission I couldn't use the easyinstall (note that python3 complains that it cannot find CARLA egg file), instead used pip3 install -U -r ~/AutonomousDriving/CARLA/PythonAPI/carla/requirements.txt. Next the import fails on ColorConverter, which is a known issue. Adding the PythonAPI to PYTHONPATH helps. I had Carla already installed in ~/AutonomousDriving/CARLA/.Tried python3 main.py -benchmark -synchronous -fps 24-weights weights/ -config benchmark_config_v1.json Town02, but this fails on import carla.

Also update-metadata (as suggested in the documentation) doesn't work.

With python2.7 I couldn't add a name to upload command.

The epoch_val_loss reached its minimum value after 30k training. It seems that the training converged nicely after 10 epochs / 15k trainings.

That works, I could inspect logfile with more detail.

Maybe I should also upload them to TensorBoard Dev to inspect them.

Could not scroll to the output in tmux.

The last tree epochs the val_loss didn't improve anymore (converged to a value of 0.36897). Still, got Failed to find CARLA directory, followed by hanging on INFO: listening to server 127.0.0.1:2000 December 21, 2020 With the egg unpacked the benchmark starts.

Switched back to MCAS (python3.7) environment.

After that still from import load_model failed (also after installing pip install keras=2.4.3). For tensorflow version 2.3.0 was required, while python3.5 had only 1.14.0.

Some packages were missing, so installed pip install pygame=1.9.6.

Had to remove some python3.7 specific print statements. Unzipped the egg file (in /tmp and copied the /tmp/carla contents into ~/AutonomousDriving/CARLA/PythonAPI/carla.

Within a the 'empty' MCAS35 environment, still the CARLA egg could be read (while python version was 3.5.5).

First tried it by modifying the given MCAS.yml, but that gave too many conflicts.

Created an 'empty' conda-environment for python3.5.

Installed Anaconda3-2020 and created the MCAS from the new MCAS.yml file.

Tried some of the tricks suggested in the forum, but to no avail.

#Hotswitch between xorg and wayland software

CarlaUE4.sh fails on warning: Not allowed to force software rendering when API explicitly selects a hardware device.

The command python3 main.py -benchmark -synchronous -fps 24 -weights weights/ -config benchmark_config_v1.json Town02 starts nicely, but waits on a CARLA simulation to start.

Code assumes that the CARLA directory is installed next to the code, so I made a symbolic link in my ~/git to the latest CARLA directory (the egg-file is loaded in multiple *.py files.

The code now nicely complains when it cannot find the correct egg file.

Tested Thomas van Orden's code with Carla 0.9.9.

As my research concentrates on the perception part of Robotics, my research is in the Informatics Institute part of the Computer Vision group.