Hi, I’m really beginner of neural network library.
I have torch7 learned model saved as model.t7 and I want to extract feature of a image image.jpg.
Following is what I did:
from torch.utils.serialization import load_lua

x = load_lua('model.t7')
print(x)

output
{'mean': [0.5657177752729754, 0.5381838567195789, 0.4972228365504561],
 'std': [0.29023818639817184, 0.2874722565279285, 0.2933830104791508],
 'model': nn.Sequential {
   [input -> (0) -> (1) -> (2) -> (3) -> (4) -> (5) -> (6) -> (7) -> (8) -> (9) -> (10) -> (11) -> (12) -> (13) -> (14) -> (15) -> (16) -> (17) -> (18) -> (19) -> (20) -> (21) -> (22) -> (23) -> (24) -> output]
   (0): nn.SpatialConvolution(3 -> 64, 3x3, 1, 1, 1, 1)
   (1): nn.ReLU
   (2): nn.SpatialConvolution(64 -> 64, 3x3, 1, 1, 1, 1)
   (3): nn.ReLU
   (4): nn.Dropout(0.2500)
   (5): nn.SpatialMaxPooling(4x4, 4, 4)
   (6): nn.SpatialBatchNormalization
   (7): nn.SpatialConvolution(64 -> 128, 3x3, 1, 1, 1, 1)
   (8): nn.ReLU
   (9): nn.SpatialConvolution(128 -> 128, 3x3, 1, 1, 1, 1)
   (10): nn.ReLU
   (11): nn.Dropout(0.2500)
   (12): nn.SpatialMaxPooling(4x4, 4, 4)
   (13): nn.SpatialBatchNormalization
   (14): nn.SpatialConvolution(128 -> 256, 3x3, 1, 1, 1, 1)
   (15): nn.ReLU
   (16): nn.SpatialConvolution(256 -> 256, 3x3, 1, 1, 1, 1)
   (17): nn.ReLU
   (18): nn.Dropout(0.2500)
   (19): nn.SpatialMaxPooling(4x4, 4, 4)
   (20): nn.SpatialBatchNormalization
   (21): nn.SpatialConvolution(256 -> 128, 1x1)
   (22): nn.ReLU
   (23): nn.Reshape(3072)
   (24): nn.Linear(3072 -> 128)
 }}

It seems I succesfullly loaded the learned network.
Then what do I have to do to extract 128 dimensional feature vector of image.jpg?