def loader(file):
"""Resize and crop image to required dims and return as FP32 array."""
image = cv2.imread(file)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
w, h = (224, 224)
image = resize_with_aspectratio(image, h, w)
image = center_crop(image, h, w)
image = np.asarray(image, dtype='float32')
# Transpose.
image = image.transpose([2, 0, 1])
return image
def loader(file):
image = cv2.imread(file)
image = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
w, h = (224, 224)
image = resize_with_aspectratio(image, h, w)
image = center_crop(image, h, w)
image = np.asarray(image, dtype='float32')
# Normalize image.
means = np.array([123.68, 116.78, 103.94], dtype=np.float32)
image -= means
# Transpose.
image = image.transpose([2, 0, 1])
return image
def loader(file):
img = Image.open(file)
img = img.convert('RGB')
img = resize_with_aspectratio(img, 256)
img = center_crop(img, (224, 224))
img = np.asarray(img, dtype='float32')
img /= 255.0
mean = np.array([0.485,0.456,0.406], dtype=np.float32)
std = np.array([0.229,0.224,0.225], dtype=np.float32)
img = (img - mean) / std
img = img.transpose([2, 0, 1])
#img = np.asarray(img.reshape((3,224,224)), dtype='float32')
return img