OpenAI CLIP vs. MetaCLIP: Compared and Contrasted

Models



OpenAI CLIP vs. MetaCLIP

Both

OpenAI CLIP

and

MetaCLIP

are commonly used in computer vision projects. Below, we compare and contrast

OpenAI CLIP

and

MetaCLIP

	OpenAI CLIP	MetaCLIP
Date of Release	Jan 05, 2021
Model Type	Classification	Classification
Architecture
GitHub Stars	11000

Compare CLIP and MetaCLIP with Autodistill

Using Autodistill, you can compare CLIP and MetaCLIP on your own images in a few lines of code.

First, install the required dependencies:


pip install autodistill autodistill-clip autodistill-metaclip

Then, create a new Python file and add the following code:


from autodistill_metaclip import MetaCLIP
from autodistill_clip import CLIP

from autodistill.detection import CaptionOntology

classes = ["solar panel", "building"]

ontology = CaptionOntology(
    {
        "solar panel": "solar panel",
        "building": "building"
    }
)

metaclip_model = MetaCLIP(ontology=ontology)
clip_model = CLIP(ontology=ontology)

metaclip_results = metaclip_model.predict("./image.png", confidence=0)
clip_results = clip_model.predict("./image.png", confidence=0)

metaclip_classes = [classes[i] for i in metaclip_results.class_id.tolist()]
metaclip_scores = metaclip_results.confidence.tolist()

print("MetaCLIP Classes:", metaclip_classes)
print("MetaCLIP Scores:", metaclip_scores)

clip_classes = [classes[i] for i in clip_results.class_id.tolist()]
clip_scores = clip_results.confidence.tolist()

print("CLIP Classes:", clip_classes)
print("CLIP Scores:", clip_scores)

When you run the file, you will see an output that shows the results from the comparison:


MetaCLIP Classes: ['solar panel', 'building']
MetaCLIP Scores: [0.6350001096725464, 0.3649998903274536]
CLIP Classes: ['solar panel']
CLIP Scores: [0.6350001096725464]

OpenAI CLIP

CLIP (Contrastive Language-Image Pre-Training) is an impressive multimodal zero-shot image classifier that achieves impressive results in a wide range of domains with no fine-tuning. It applies the recent advancements in large-scale transformers like GPT-3 to the vision arena.

How to Augment How to Label How to Plot Predictions How to Filter Predictions How to Create a Confusion Matrix