Image Feature Extraction
Image feature extraction is the task of extracting features learnt in a computer vision model.
Dimension 1 | Dimension 2 | Dimension 3 |
---|---|---|
0.21236686408519745 | 1.0919708013534546 | 0.8512550592422485 |
0.809657871723175 | -0.18544459342956543 | -0.7851548194885254 |
1.3103108406066895 | -0.2479034662246704 | -0.9107287526130676 |
1.8536205291748047 | -0.36419737339019775 | 0.09717650711536407 |
About Image Feature Extraction
Use Cases
Transfer Learning
Models trained on a specific dataset can learn features about the data. For instance, a model trained on a car classification dataset learns to recognize edges and curves on a very high level and car-specific features on a low level. This information can be transferred to a new model that is going to be trained on classifying trucks. This process of extracting features and transferring to another model is called transfer learning.
Similarity
Features extracted from models contain semantically meaningful information about the world. These features can be used to detect the similarity between two images. Assume there are two images: a photo of a stray cat in a street setting and a photo of a cat at home. These images both contain cats, and the features will contain the information that there's a cat in the image. Thus, comparing the features of a stray cat photo to the features of a domestic cat photo will result in higher similarity compared to any other image that doesn't contain any cats.
Inference
import torch
from transformers import pipeline
pipe = pipeline(task="image-feature-extraction", model_name="google/vit-base-patch16-384", framework="pt", pool=True)
pipe("https://huggingface.co/datasets/huggingface/documentation-images/resolve/main/cats.png")
feature_extractor(text,return_tensors = "pt")[0].numpy().mean(axis=0)
'[[[0.21236686408519745, 1.0919708013534546, 0.8512550592422485, ...]]]'
Compatible libraries
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Note A powerful image feature extraction model.
Note A strong image feature extraction model.
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Note Strong image feature extraction model made for information retrieval from documents.
Note Strong image feature extraction model that can be used on images and documents.
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