colipri

18
license:mit
by
microsoft
Image Model
OTHER
New
0 downloads
Early-stage
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Quick Summary

AI model with specialized capabilities.

Code Examples

Zero-shot classificationpython
>>> from colipri import ZeroShotImageClassificationPipeline
>>> pipeline = ZeroShotImageClassificationPipeline(model, processor)
>>> pipeline(image, ["No lung nodules", "Lung nodules"])
[
    {'score': 0.005, 'label': 'No lung nodules'},
    {'score': 0.995, 'label': 'Lung nodules'}
]
Feature extractionpythonpytorch
>>> import torch
>>> preprocessed_images = processor.process_images(image)
>>> preprocessed_images[0]
ScalarImage(shape: (1, 192, 192, 192); spacing: (2.00, 2.00, 2.00); orientation: SAR+; dtype: torch.FloatTensor; memory: 27.0 MiB)
>>> images_batch = processor.to_images_batch(preprocessed_images)
images_batch.shape
torch.Size([1, 1, 192, 192, 192])
>>> with torch.no_grad():
...     patch_embeddings = model.encode_image(images_batch)
>>> patch_embeddings.shape
torch.Size([1, 768, 24, 24, 24])
>>> with torch.no_grad():
...     pooled_embeddings = model.encode_image(images_batch, pool=True, project=True)
>>> pooled_embeddings.shape
torch.Size([1, 768])

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