We are aim to a world where visually impaired are able to choice and enjoy drink what they want.
Of the many canned drinks, there are only two types of drinks that can be classified in braille: 'just drink' and 'soda'. This is what canned drinks look like from a visually impaired's point of view. So we created a service that helps visually impaired people choose their favorite drinks.
With CanDrink, visually impaired can get free of the inconvenience of failure of recognizing cans
You can see more detail on YouYube!
Click image to see more detail!
- Find out the brand
- Search the drink
- Check the expiration date
CanDrink Server
git clone https://github.com/GDSC-DEU/2022-SolutionChallenge-CanDrink
cd serverdocker-compose upapp
├─ routes
│ ├─ views.py
├─ tffile
│ ├─ models #model files
├─ main.py
├─ run.pyObject detection is run with TensorFlow Lite. Model files will be distributed with constant updates. Therefore, we added deploy server for model file distribution. Client checks model is updated and download from server.
You need flutter SDK to run this project.
See Flutter Installation.
git clone https://github.com/GDSC-DEU/2022-SolutionChallenge-CanDrink
cd client
code .
And you can see VSCode with this project.
Press F5 to run on VSCode.
git clone https://github.com/GDSC-DEU/2022-SolutionChallenge-CanDrink
pip install -r requirements.txt
echo "KEYWORD=[serch keyword]" >> .env
echo "KEY=[save key]" >> .env
echo "NAME=[forlder name]" >> .env
python crawler.py
- OS: Ubuntu 20.04.4 LTS x86_64
- CPU: 11th Gen Intel CPU
- GPU: NVIDIA 3080 Ti with 12GB VRAM
- GPU Driver Version: 470.129.06
- CUDA Version: 11.2
- cuDNN Version: 8.1.0
If you have nvidia GPU, you can accelerate training speed rapidly. This section tells you how to set up a GPU. For more details about requirements, please see TensorFlow Installation Guide
Go to https://www.nvidia.com/en-us/geforce/drivers/ and scroll down to MANUAL DRIVER SEARCH, search your GPU's driver. You can find various versions i.e. 470, 510
TensorFlow requires 450.80.02+, but closest version may get better result.
After complete download, run file as root.
sudo sh NVIDIA-Linux-x86_64-470.129.06.run... Occasionally you can see this error:
An NVIDIA kernel module 'nvidia-drm' appears to already be loaded ...
Please ensure GUI is disabled. If you are using Ubuntu Desktop 20.04, sudo service gdm3 stop helps to resolve this error.
Go to https://developer.nvidia.com/cuda-11.2.0-download-archive?target_os=Linux&target_arch=x86_64&target_distro=Ubuntu&target_version=2004&target_type=runfilelocal and check your OS and architecture. Select Installer Type to runtime (local) and follow the instruction.
Note: You must uncheck nvidia-driver-460, this option may causes installation error.
Go to nvidia cuDNN archive: https://developer.nvidia.com/rdp/cudnn-archive and download 8.1.0 for CUDA 11.0, 11.1 and 11.2.
Use nvidia-smi command to check driver version and CUDA version.
... And run python code below for ensure the tensorflow correctly recognize your GPU device.
>>> import tensorflow as tf
>>> tf.config.list_physical_devices('GPU')When installation was successfully done, you can see following result:
[PhysicalDevice(name='/physical_device:GPU:0', device_type='GPU')]