This is the official Python client for interacting with our powerful recognition API. The Clarifai API offers image and video recognition as a service. Whether you have one image or billions, you are only steps away from using artificial intelligence to recognize your visual content.
- Try the Clarifai demo at: https://clarifai.com/demo
- Sign up for a free account at: https://clarifai.com/developer/account/signup/
- Read the developer guide at: https://clarifai.com/developer/guide/
Install the API client:
pip install clarifai --upgrade
Note: If you cannot use
pip, you can download the latest release manually or using git.
Firstly, generate your Clarifai API key on the API keys page. The client uses it for authentication.
Then, to authenticate, either:
- initialize the
ClarifaiAppwith your API keyfrom clarifai.rest import ClarifaiApp app = ClarifaiApp(api_key='YOUR_API_KEY')
- or set the environment variable named
CLARIFAI_API_KEY - or run the script
./scripts/clarifai configwhich will, after you input the API key, create a file~/.clarifai/configwith your key
Note: If you have both the environmental variable CLARIFAI_API_KEY and a file
~/.clarifai/config, the environmental variable will be used.
For AWS or Windows users, please refer to the documentation for more instructions.
The following example will setup the client and predict concepts on an image from a URL, using the general model
from clarifai.rest import ClarifaiApp
app = ClarifaiApp()
model = app.public_models.general_model
response = model.predict_by_url(url='https://samples.clarifai.com/metro-north.jpg')Use model.predict_by_filename to predict concepts on a local file.
The response is a JSON structure. Here's how to print all the predicted concepts associated with the image, together with their confidence values.
concepts = response['outputs'][0]['data']['concepts']
for concept in concepts:
print(concept['name'], concept['value'])See many more code examples in the developer guide and in the Python client tutorial.
Also see the Python client reference.