Readme
Cog model that outputs clip-vit-large-patch14 features for text and images.
Run with the API:
import replicate
import numpy as np
from numpy.linalg import norm
def cos_sim(a, b):
return np.dot(a, b) / (norm(a) * norm(b))
inputs = """
a photo of a dog
a cat
two cats with remote controls
https://replicate.com/api/models/cjwbw/clip-vit-large-patch14/files/36b04aec-efe2-4dea-9c9d-a5faca68b2b2/000000039769.jpg
"""
# run prediction
model = replicate.models.get("andreasjansson/clip-features")
outputs = model.predict(inputs=inputs)
# output similarity of the three text lines with the image on line 4
for i in range(3):
print(outputs[i]["input"])
print(cos_sim(outputs[i]["embedding"], outputs[3]["embedding"]))
print()
"""
# run prediction
model = replicate.models.get("andreasjansson/clip-features")
outputs = model.predict(inputs=inputs)
# output similarity of the three text lines with the image on line 4
for i in range(3):
print(outputs[i].input)
print(cos_sim(outputs[i].embedding, outputs[3].embedding))
print()
