|
@ -18,11 +18,12 @@ import torch |
|
|
from torchvision import transforms |
|
|
from torchvision import transforms |
|
|
import sys |
|
|
import sys |
|
|
from pathlib import Path |
|
|
from pathlib import Path |
|
|
|
|
|
import numpy |
|
|
|
|
|
|
|
|
from towhee.operator import Operator |
|
|
from towhee.operator import Operator |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
class EfficientnetEmbeddingOperator(Operator): |
|
|
|
|
|
|
|
|
class EfficientnetImageEmbeddingOperator(Operator): |
|
|
""" |
|
|
""" |
|
|
Embedding extractor using efficientnet. |
|
|
Embedding extractor using efficientnet. |
|
|
Args: |
|
|
Args: |
|
@ -41,8 +42,9 @@ class EfficientnetEmbeddingOperator(Operator): |
|
|
self.tfms = transforms.Compose([transforms.Resize(224), transforms.ToTensor(), |
|
|
self.tfms = transforms.Compose([transforms.Resize(224), transforms.ToTensor(), |
|
|
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]) |
|
|
transforms.Normalize([0.485, 0.456, 0.406], [0.229, 0.224, 0.225]), ]) |
|
|
|
|
|
|
|
|
def __call__(self, img_path: str) -> NamedTuple('Outputs', [('embedding', torch.Tensor)]): |
|
|
|
|
|
|
|
|
def __call__(self, img_path: str) -> NamedTuple('Outputs', [('feature_vector', numpy.ndarray)]): |
|
|
Outputs = NamedTuple('Outputs', [('embedding', torch.Tensor)]) |
|
|
Outputs = NamedTuple('Outputs', [('embedding', torch.Tensor)]) |
|
|
img = self.tfms(Image.open(img_path)).unsqueeze(0) |
|
|
img = self.tfms(Image.open(img_path)).unsqueeze(0) |
|
|
features = self.model._model.extract_features(img) |
|
|
features = self.model._model.extract_features(img) |
|
|
|
|
|
Outputs = NamedTuple('Outputs', [('feature_vector', numpy.ndarray)]) |
|
|
return Outputs(features.flatten().detach().numpy()) |
|
|
return Outputs(features.flatten().detach().numpy()) |
|
|