def __getitem__(self, idx):
########################################################################
# TODO: #
# Return the idx sample in the Dataset. A simple should be a dictionary#
# where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
########################################################################
image = get_image(idx, self.key_pts_frame)
img_shape = image.shape
image = image.reshape(1, img_shape[0], img_shape[1])
keypoints = get_keypoints(idx, self.key_pts_frame)
sample = {'image': image, 'keypoints': keypoints}
########################################################################
# END OF YOUR CODE #
########################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx):
########################################################################
# TODO: #
# Return the idx sample in the Dataset. A simple should be a dictionary#
# where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
########################################################################
image = get_image(idx, self.key_pts_frame)
rows, columns = image.shape
image = image.reshape(1, rows, columns)
keypoints = self.key_pts_frame.iloc[
idx, self.key_pts_frame.columns != 'Image']
keypoints = np.array([keypoints])
keypoints = keypoints.astype('float').reshape(-1, 2)
sample = {'image': image, 'keypoints': keypoints}
########################################################################
# END OF YOUR CODE #
########################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx, verbose=False):
sample = {'image': None, 'keypoints': None}
#######################################################################
# TODO: #
# Return the idx sample in the Dataset. A sample should be a #
# dictionary where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
#######################################################################
image = get_image(idx, self.key_pts_frame)
image = image[np.newaxis, :]
landmarks = get_keypoints(idx, self.key_pts_frame)
if verbose:
print("-------------------------")
print("Dataloader")
print("idx: " + str(idx))
print("img shape: " + str(image.shape))
print("landmarks: " + str(landmarks.shape))
print(landmarks)
print("-------------------------")
sample = {'image': image, 'keypoints': landmarks}
#######################################################################
# END OF YOUR CODE #
#######################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx):
sample = {'image': None, 'keypoints': None}
#######################################################################
# TODO: #
# Return the idx sample in the Dataset. A sample should be a #
# dictionary where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
#######################################################################
from exercise_code.data_utils import get_keypoints
from exercise_code.data_utils import get_image
# sample['image'] = np.array([get_image(idx, self.key_pts_frame)])
# from (96, 96) to (1, 96, 96)
sample['image'] = get_image(idx, self.key_pts_frame)[np.newaxis, :]
sample['keypoints'] = get_keypoints(idx, self.key_pts_frame)
#######################################################################
# END OF YOUR CODE #
#######################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx):
########################################################################
# TODO: #
# Return the idx sample in the Dataset. A simple should be a dictionary#
# where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
# You can use mpimg.imread(image path) to read out image data #
########################################################################
from exercise_code.data_utils import get_keypoints
from exercise_code.data_utils import get_image
sample = {}
sample['image'] = np.array([get_image(idx, self.key_pts_frame)])
sample['keypoints'] = get_keypoints(idx, self.key_pts_frame)
########################################################################
# END OF YOUR CODE #
########################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx):
########################################################################
# TODO: #
# Return the idx sample in the Dataset. A simple should be a dictionary#
# where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
# You can use mpimg.imread(image path) to read out image data #
########################################################################
sample = {
'image': np.expand_dims(get_image(idx, self.key_pts_frame), 0),
'keypoints': get_keypoints(idx, self.key_pts_frame)
}
########################################################################
# END OF YOUR CODE #
########################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx):
sample = {'image': None, 'keypoints': None}
#######################################################################
# TODO: #
# Return the idx sample in the Dataset. A sample should be a #
# dictionary where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
#######################################################################
image = np.array([get_image(idx, self.key_pts_frame)])
keypoints = get_keypoints(idx, self.key_pts_frame)
sample = {'image': image, 'keypoints': keypoints}
#######################################################################
# END OF YOUR CODE #
#######################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx):
sample = {'image': None, 'keypoints': None}
#######################################################################
# TODO: #
# Return the idx sample in the Dataset. A sample should be a #
# dictionary where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_keypoints, 2]} #
#######################################################################
from exercise_code.data_utils import get_keypoints, get_image
sample = {}
sample["image"] = get_image(idx,
self.key_pts_frame).reshape(-1, 96, 96)
sample["keypoints"] = get_keypoints(idx, self.key_pts_frame)
#######################################################################
# END OF YOUR CODE #
#######################################################################
if self.transform:
sample = self.transform(sample)
return sample
def __getitem__(self, idx):
########################################################################
# TODO: #
# Return the idx sample in the Dataset. A simple should be a dictionary#
# where the key, value should be like #
# {'image': image of shape [C, H, W], #
# 'keypoints': keypoints of shape [num_Normalize()keypoints, 2]} #
# You can use mpimg.imread(image path) to read out image data #
########################################################################
#self.key_pts_frame
map = {}
image = get_image(idx, self.key_pts_frame)
image = np.array(image)
image = np.reshape(image, (1, image.shape[0], image.shape[1]))
key_pts = get_keypoints(idx, self.key_pts_frame)
map['image'] = image
map['keypoints'] = np.float_(key_pts)
t = self.transform
if (t is not None):
map = t(map)
return (map)
pass
########################################################################
# END OF YOUR CODE #
########################################################################
if self.transform:
sample = self.transform(sample)
return sample
# In[ ]:
key_pts_frame.dropna(inplace=True)
key_pts_frame.describe().loc['count'].plot.bar()
print(key_pts_frame.shape)
# In[ ]:
from exercise_code.data_utils import get_keypoints
from exercise_code.data_utils import get_image
n = 0
image = get_image(n, key_pts_frame)
keypoints = get_keypoints(n, key_pts_frame)
print('image size: {}'.format(image.shape))
print('keypoints size: {}'.format(keypoints.shape))
# Below, is a function `show_all_keypoints` that takes in an image and keypoints and displays them. As you look at this data, **note that these images are not all of the same quality**!
# In[ ]:
# select an image by index in our data frame
for n in range(5):
image = get_image(n, key_pts_frame)
key_pts = get_keypoints(n, key_pts_frame)
show_all_keypoints(image, key_pts)