coca.md

Example Usage Script: Interrogating Images with LAION-CoCa

In this example, we will demonstrate how to use LAION-CoCa to generate captions for an image.

Import Required Libraries

We start by importing the necessary libraries:

from PIL import Image
from nataili.clip import CoCa
from nataili.model_manager.clip import ClipModelManager
from nataili.util.logger import logger

Image from the Python Imaging Library (PIL) is used to open the image files. CoCa from the nataili.clip module is the service class used to generate captions for the images. ClipModelManager from the nataili.model_manager.clip module is the model manager used to download and manage the CLIP model. logger from the nataili.util.logger module is used to log the results.

Open the Image

Next, we open the image file:

image = Image.open("01.png")

Replace "01.png" with the path to the image file you want to use.

Create an Instance of the Model Manager

We create an instance of the ClipModelManager:

mm = ClipModelManager()

Load the CoCa Model

We use the load function of the model manager to download and load the CoCa model:

mm.load("coca_ViT-L-14")

The "coca_ViT-L-14" argument is the key used to identify the CoCa model in the model database.

Create a CoCa Object

We create a CoCa object, passing in the loaded CoCa model and related information:

coca = CoCa(
    mm.loaded_models["coca_ViT-L-14"]["model"],
    mm.loaded_models["coca_ViT-L-14"]["transform"],
    mm.loaded_models["coca_ViT-L-14"]["device"],
    mm.loaded_models["coca_ViT-L-14"]["half_precision"],
)

Generate the Caption

We use the __call__ function of the CoCa object to generate the caption for the image:

logger.generation(coca(image))

The results will be logged using the logger object. The format of the log message is "caption: [generated caption]".

With these steps, we have successfully used LAION-CoCa to generate captions for an image.