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from skimage import io, transform
from multiprocessing.dummy import Pool as ThreadPool
def rescale(root_new, root_old, img_path, ann_path, out_shape):
try:
img = io.imread(root_old+"/"+img_path)
except Exception as E:
print E
h, w, _ = img.shape
f_h, f_w = float(out_shape)/h, float(out_shape)/w
trans_img = transform.rescale(img, (f_h, f_w))
num_objs = 0
with open(root_old+"/"+ann_path, 'r') as f:
ann = f.readline()
ann = ann.rstrip()
ann = ann.split(' ')
ann = [float(i) for i in ann]
num_objs = len(ann) / 5
for idx in xrange(num_objs):
ann[idx * 5 + 0] = int(f_w * ann[idx * 5 + 0])
ann[idx * 5 + 1] = int(f_h * ann[idx * 5 + 1])
ann[idx * 5 + 2] = int(f_w * ann[idx * 5 + 2])
ann[idx * 5 + 3] = int(f_h * ann[idx * 5 + 3])
# Write the new annotations to file
with open(root_new+"/"+ann_path, 'w') as f_new:
for val in ann:
f_new.write(str(val)+' ')
# Save the new image
io.imwrite(root_new+"/"+img_path, trans_img)
def preprocess():
source = '/users2/Datasets/PASCAL_VOC/VOCdevkit/VOC2012_Resize/source.txt'
root_old = '/users2/Datasets/PASCAL_VOC/VOCdevkit/VOC2012'
root_new = '/users2/Datasets/PASCAL_VOC/VOCdevkit/VOC2012_Resize'
out_shape = 416
with open(source, 'r') as src:
lines = src.readlines()
print 'Processing {} images and annotations'.format(len(lines))
for line in lines:
line = line.rstrip()
line = line.split(' ')
img_path = line[0]
ann_path = line[1]
rescale(root_new, root_old, img_path, ann_path, out_shape)
if __name__ == '__main__':
preprocess()
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