def resize_and_save(df, img_name, true_idx, size='80x50', fraction=0.125):
'''
INPUT: (1) Pandas DF
(2) string: image name
(3) integer: the true index in the df of the image
(4) string: to append to filename
(5) float: fraction to scale images by
OUTPUT: None
Resize and save the images in a new directory.
Try to read the image. If it fails, download it to the raw data directory.
Finally, read in the full size image and resize it.
'''
try:
img = imread(img_name)
except:
cardinal_dir = img_name[-5:-4]
cardinal_translation = {'N': 0, 'E': 90, 'S': 180, 'W': 270}
coord = (df.ix[true_idx]['lat'], df.ix[true_idx]['lng'])
print 'Saving new image...'
print coord, cardinal_dir, cardinal_translation[cardinal_dir]
save_image(coord, cardinal_translation[cardinal_dir], loc='newdata')
finally:
img_name_to_write = ('newdata_' + size + '/' +
img_name[8:-4] + size + '.png')
if os.path.isfile(img_name_to_write) == False:
img = imread(img_name)
resized = imresize(img, fraction)
print 'Writing file...'
imsave(img_name_to_write, resized)
def resize_and_save(df, img_name, true_idx, size='80x50', fraction=0.125):
'''
INPUT: (1) Pandas DF
(2) string: image name
(3) integer: the true index in the df of the image
(4) string: to append to filename
(5) float: fraction to scale images by
OUTPUT: None
Resize and save the images in a new directory.
Try to read the image. If it fails, download it to the raw data directory.
Finally, read in the full size image and resize it.
'''
try:
img = imread(img_name)
except:
cardinal_dir = img_name[-5:-4]
cardinal_translation = {'N': 0, 'E': 90, 'S': 180, 'W': 270}
coord = (df.ix[true_idx]['lat'], df.ix[true_idx]['lng'])
print 'Saving new image...'
print coord, cardinal_dir, cardinal_translation[cardinal_dir]
save_image(coord, cardinal_translation[cardinal_dir], loc='newdata')
finally:
img_name_to_write = ('newdata_' + size + '/' + img_name[8:-4] + size +
'.png')
if os.path.isfile(img_name_to_write) == False:
img = imread(img_name)
resized = imresize(img, fraction)
print 'Writing file...'
imsave(img_name_to_write, resized)
def download_images(df, loc='newdata'):
'''
INPUT: (1) Pandas DataFrame with locations to download images
(2) string: what folder to save new images to
OUTPUT: None
Download images from Google Maps Streetview API using
the function defined in imageScraper.
The API maxes out at 25000 images a day (6250 total locations,
NESW for each location)
'''
how_many_images_downloaded = 0
for lt, lg in zip(df['lat'][14244:], df['lng'][14244:]):
for heading in [0, 90, 180, 270]:
print how_many_images_downloaded
how_many_images_downloaded += 1
save_image((lt, lg), heading, loc=loc)
def download_images(df, loc='newdata'):
'''
INPUT: (1) Pandas DataFrame with locations to download images
(2) string: what folder to save new images to
OUTPUT: None
Download images from Google Maps Streetview API using
the function defined in imageScraper.
The API maxes out at 25000 images a day (6250 total locations,
NESW for each location)
'''
how_many_images_downloaded = 0
for lt, lg in zip(df['lat'][14244:], df['lng'][14244:]):
for heading in [0, 90, 180, 270]:
print how_many_images_downloaded
how_many_images_downloaded += 1
save_image((lt, lg), heading, loc=loc)