- Counts specified Objects on a Image and writes the Count to a MariaDB Database.
- Choose between different Models:
- GPU Support
- Configurable via Web Interface
- REST API with Swagger Documentation for easy external Data Access.
Tech | Description |
---|---|
Docker | |
PowerShell Core | |
PowerShell Module Pode | |
Python | |
... AI Stuff to be filled ... |
- docker
- docker-compose
- x64 or ARMv8 System
- min 4 GB free Memory (depending on AI Model)
git clone https://github.com/NopeNix/ai-counter.git
(The docker-compose.yml
also works with Portainer)
docker compose up -d
ALTERNATIVE FOR DEV use docker compose watch:
docker compose watch
(this will automatically rebuild / sync files when there are changes)
python main.py --url image_url --model model_path
The model_path
is optional. By default, it uses the https://tfhub.dev/google/openimages_v4/ssd/mobilenet_v2/1
model. You can also try the tensorflow/efficientdet/tensorFlow2/d0
model.
--include-picture-with-boundingboxes
: If you want to include the picture with the bounding boxes. This adds aimage-base64-encoded
key with a base64 encoded image encoded inutf-8
.--filter
: If you want to filter the objects that are detected. For example,--filter "person,car"
will only return the labels that areperson
orcar
(make sure to check out the labels supported by the models). Separate the labels with a comma, don't use spaces, and don't forget to wrap the labels with quotes.--min-confidence
: The minimum confidence for the model to consider the object detected.