Vision Microservice: LaMa Inpainting

Deploys simple-lama-inpainting as a microservice. The microservice uses an Ubuntu 20.04.6 LTS container (see below for more system information).

Requirements

Luckily, base Ubuntu 20.04 has all that's needed. The remaining requirements are Python packages. venv is used to avoid cluttering the system (optional).

If you do not have the venv package, it is recommended to install it through the system package manager:

# apt install python3.8-venv

Note: If you use simple_lama and run into the following error, you may need to apt install libgl1.

ImportError: libGL.so.1: cannot open shared object file: No such file or directory

Server Deployment

Helper Script

$ ./deploy.sh

Manual

1. Create and activate the venv (optional)

$ python3 -m venv .venv
$ source .venv/bin/activate # for bash/zsh

2. Install the required packages

$ pip install simple-lama-inpainting

3. Start the Flask server:

$ flask run

Testing

After deploying the server, ./send_request.py sends test_im.png and test_mask.png in the current directory to the server. The result will be saved as result.png.

Note: send_request.py assumes the hostname is http://127.0.0.1:5000. Make sure to modify host if needed.

System info

(.venv) osalbahr@12841f99a914:~$ fastfetch 
                            ....    
              .',:clooo:  .:looooo:.    
           .;looooooooc  .oooooooooo'    
        .;looooool:,''.  :ooooooooooc    
       ;looool;.         'oooooooooo,    
      ;clool'             .cooooooc.  ,,    
         ...                ......  .:oo,    
  .;clol:,.                        .loooo'     osalbahr@12841f99a914
 :ooooooooo,                        'ooool     ---------------------
'ooooooooooo.                        loooo.    OS: Ubuntu focal 20.04 x86_64
'ooooooooool                         coooo.    Host: Alienware Aurora R9 (1.0.7)
 ,loooooooc.                        .loooo.    Kernel: 6.2.0-34-generic
   .,;;;'.                          ;ooooc     Uptime: 33 days, 6 hours, 32 mins
       ...                         ,ooool.     Packages: 358 (dpkg), 33 (brew)
    .cooooc.              ..',,'.  .cooo.      Shell: bash 5.0.17
      ;ooooo:.           ;oooooooc.  :l.       Terminal: node
       .coooooc,..      coooooooooo.           CPU: Intel(R) Core(TM) i9-9900K (16) @ 5.00 GHz
         .:ooooooolc:. .ooooooooooo'           Memory: 24.37 GiB / 62.61 GiB (39%)
           .':loooooo;  ,oooooooooc            Disk (/): 200.92 GiB / 1.83 TiB (11%) - overlay
               ..';::c'  .;loooo:'             Locale: en_US.UTF-8
                             .
                                               ████████████████████████
                                               ████████████████████████





(.venv) osalbahr@12841f99a914:~$ nvidia-smi 
Tue Nov 14 01:06:38 2023       
+---------------------------------------------------------------------------------------+
| NVIDIA-SMI 535.113.01             Driver Version: 535.113.01   CUDA Version: 12.2     |
|-----------------------------------------+----------------------+----------------------+
| GPU  Name                 Persistence-M | Bus-Id        Disp.A | Volatile Uncorr. ECC |
| Fan  Temp   Perf          Pwr:Usage/Cap |         Memory-Usage | GPU-Util  Compute M. |
|                                         |                      |               MIG M. |
|=========================================+======================+======================|
|   0  NVIDIA GeForce RTX 2080 ...    Off | 00000000:01:00.0 Off |                  N/A |
| 18%   29C    P8              16W / 250W |     15MiB /  8192MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
|   1  NVIDIA GeForce RTX 2080 ...    Off | 00000000:02:00.0 Off |                  N/A |
| 18%   28C    P8              13W / 250W |      6MiB /  8192MiB |      0%      Default |
|                                         |                      |                  N/A |
+-----------------------------------------+----------------------+----------------------+
                                                                                         
+---------------------------------------------------------------------------------------+
| Processes:                                                                            |
|  GPU   GI   CI        PID   Type   Process name                            GPU Memory |
|        ID   ID                                                             Usage      |
|=======================================================================================|
+---------------------------------------------------------------------------------------+