Ejemplo n.º 1
0
 def load_data(self, filename):
     """
     load_data
     """
     image = process_image(filename, 224)
     tensor = core.PaddleTensor()
     print(len(image))
     tensor.shape = [1, 3, 224, 224]
     tensor.data = core.PaddleBuf(image.tolist())
     tensor.dtype = core.PaddleDType.FLOAT32
     tensor.lod = [[0L, 1L]]
     return [tensor]
Ejemplo n.º 2
0
 def load_data(self, filename):
     """
     load_data
     """
     image = process_image(filename, 224)
     image_tensor = core.PaddleTensor()
     image_tensor.name = 'image'
     image_tensor.shape = [1, 3, 224, 224]
     image_tensor.data = core.PaddleBuf(image.tolist())
     image_tensor.dtype = core.PaddleDType.FLOAT32
     #im-info
     im_info_tensor = core.PaddleTensor()
     im_info_tensor.shape = [1, 3]
     im_info_tensor.name = "im_info"
     im_info_tensor.data = core.PaddleBuf([224., 224., 1.0])
     im_info_tensor.dtype = core.PaddleDType.FLOAT32
     return [image_tensor, im_info_tensor]
Ejemplo n.º 3
0
 def images_to_tensor(self):
     images = []
     for file in sorted(os.listdir('data/jaffe_images_small')):
         if (file != '.DS_Store'):
             image = matplotlib.image.imread('data/jaffe_images_small/' +
                                             file)  # read images
             if (len(np.shape(image)) > 2):
                 image = image[:, :, 0]
             image = image.tolist()  # convert to list ?
             image = imresize(image, (48, 48))  # compress to 48*48 pixel
             images.append(image)
     image_tensor = np.array(images)
     image_tensor = image_tensor - np.mean(image_tensor, axis=0)  # ???
     image_tensor = image_tensor.reshape(
         213, 48, 48,
         1)  # 213 images in data/jaffe_images_small, each one 48*48 pixel
     return image_tensor
Ejemplo n.º 4
0
 def load_data(self, filename):
     """
     load_data
     """
     image = process_image(filename, 224)
     image_tensor = core.PaddleTensor()
     image_tensor.name = 'image'
     image_tensor.shape = [1, 3, 224, 224]
     image_tensor.data = core.PaddleBuf(image.tolist())
     image_tensor.dtype = core.PaddleDType.FLOAT32
     #image_shspe
     im_shape_tensor = core.PaddleTensor()
     im_shape_tensor.shape = [1, 2]
     im_shape_tensor.name = "im_shape"
     im_shape_tensor.data = core.PaddleBuf([224, 224])
     im_shape_tensor.dtype = core.PaddleDType.INT32
     #im_id
     im_id_tensor = core.PaddleTensor()
     im_id_tensor.shape = [1, 1]
     im_id_tensor.name = "im_id"
     im_id_tensor.data = core.PaddleBuf([1,])
     im_id_tensor.dtype = core.PaddleDType.INT32
     return [image_tensor, im_shape_tensor]
Ejemplo n.º 5
0
import numpy as np
from scipy.misc import imresize
import matplotlib.image
import matplotlib.pyplot

image = matplotlib.image.imread('data/jaffe_images_small/NA.SA2.206.tiff')
print image
#matplotlib.pyplot.imshow(image)
image = image.tolist()
image = imresize(image, (48, 48))
print image
matplotlib.pyplot.imshow(image)