from clarifai.rest import ClarifaiApp
Define your Clarifai API key
clarifai_api_key = 'YOUR_API_KEY_HERE'
Initialize Clarifai app
app = ClarifaiApp(api_key=clarifai_api_key)
Define the B.A.T.M.A.N acronym
acronym = {
'B': 'Batman',
'A': 'Apple',
'T': 'Tree',
'M': 'Mountain',
'A': 'Airplane',
'N': 'Nature'
}
def analyze_image(image_url):
# Predict concepts in the image
response = app.models.predict('general-v1.3', url=image_url)
# Extract relevant concepts
concepts = response['outputs'][0]['data']['concepts']
# Get the top predicted concept
top_prediction = concepts[0]['name']
return top_prediction
def interpret_acronym(acronym_dict):
interpretation = {}
for letter, word in acronym_dict.items():
# Use Clarifai to analyze images associated with the word
result = analyze_image(f'https://www.google.com/search?q={word}&tbm=isch')
interpretation[letter] = result
Interpret the B.A.T.M.A.N acronym
interpreted_acronym = interpret_acronym(acronym)
Print the interpretation
for letter, word in acronym.items():
print(f'{letter} - {word} : {interpreted_acronym[letter]}')
from clarifai.rest import ClarifaiApp
Define your Clarifai API key
clarifai_api_key = 'YOUR_API_KEY_HERE'
Initialize Clarifai app
app = ClarifaiApp(api_key=clarifai_api_key)
Define the B.A.T.M.A.N acronym
acronym = {
'B': 'Batman',
'A': 'Apple',
'T': 'Tree',
'M': 'Mountain',
'A': 'Airplane',
'N': 'Nature'
}
def analyze_image(image_url):
# Predict concepts in the image
response = app.models.predict('general-v1.3', url=image_url)
def interpret_acronym(acronym_dict):
interpretation = {}
for letter, word in acronym_dict.items():
# Use Clarifai to analyze images associated with the word
result = analyze_image(f'https://www.google.com/search?q={word}&tbm=isch')
interpretation[letter] = result
Interpret the B.A.T.M.A.N acronym
interpreted_acronym = interpret_acronym(acronym)
Print the interpretation
for letter, word in acronym.items():
print(f'{letter} - {word} : {interpreted_acronym[letter]}')