Update extract_square_images
This commit is contained in:
parent
5a8156026a
commit
41b7d50944
|
@ -13,16 +13,17 @@ import torch
|
|||
def main():
|
||||
split_img = False
|
||||
opt = {}
|
||||
opt['n_thread'] = 4
|
||||
opt['compression_level'] = 98 # JPEG compression quality rating.
|
||||
opt['n_thread'] = 7
|
||||
opt['compression_level'] = 95 # JPEG compression quality rating.
|
||||
# CV_IMWRITE_PNG_COMPRESSION from 0 to 9. A higher value means a smaller size and longer
|
||||
# compression time. If read raw images during training, use 0 for faster IO speed.
|
||||
|
||||
opt['dest'] = 'file'
|
||||
opt['input_folder'] = ['F:\\4k6k\\datasets\\ns_images\\imagesets\\imageset_1024_square_with_new']
|
||||
opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\imagesets\\imageset_384_full'
|
||||
opt['imgsize'] = 384
|
||||
#opt['bottom_crop'] = 120
|
||||
opt['input_folder'] = ['F:\\4k6k\\datasets\\ns_images\\imagesets\\pn_coven\\working']
|
||||
opt['save_folder'] = 'F:\\4k6k\\datasets\\ns_images\\imagesets\\pn_coven\\cropped'
|
||||
opt['imgsize'] = 1024
|
||||
opt['bottom_crop'] = .1
|
||||
opt['keep_folder'] = True
|
||||
|
||||
save_folder = opt['save_folder']
|
||||
if not osp.exists(save_folder):
|
||||
|
@ -58,11 +59,14 @@ class TiledDataset(data.Dataset):
|
|||
# Perform explicit crops first. These are generally used to get rid of watermarks so we dont even want to
|
||||
# consider these areas of the image.
|
||||
if 'bottom_crop' in self.opt.keys():
|
||||
img = img[:-self.opt['bottom_crop'], :, :]
|
||||
bc = self.opt['bottom_crop']
|
||||
if bc > 0 and bc < 1:
|
||||
bc = int(bc * img.shape[0])
|
||||
img = img[:-bc, :, :]
|
||||
|
||||
h, w, c = img.shape
|
||||
# Uncomment to filter any image that doesnt meet a threshold size.
|
||||
if min(h,w) < 512:
|
||||
if min(h,w) < self.opt['imgsize']:
|
||||
print("Skipping due to threshold")
|
||||
return None
|
||||
|
||||
|
@ -71,7 +75,17 @@ class TiledDataset(data.Dataset):
|
|||
# Crop the image so that only the center is left, since this is often the most salient part of the image.
|
||||
img = img[(h - dim) // 2:dim + (h - dim) // 2, (w - dim) // 2:dim + (w - dim) // 2, :]
|
||||
img = cv2.resize(img, (self.opt['imgsize'], self.opt['imgsize']), interpolation=cv2.INTER_AREA)
|
||||
cv2.imwrite(osp.join(self.opt['save_folder'], basename + ".jpg"), img, [cv2.IMWRITE_JPEG_QUALITY, self.opt['compression_level']])
|
||||
output_folder = self.opt['save_folder']
|
||||
if self.opt['keep_folder']:
|
||||
# Attempt to find the folder name one level above opt['input_folder'] and use that.
|
||||
pts = [os.path.dirname(path)]
|
||||
while pts[0] != self.opt['input_folder'][0]:
|
||||
pts = os.path.split(pts[0])
|
||||
output_folder = osp.join(self.opt['save_folder'], pts[-1])
|
||||
os.makedirs(output_folder, exist_ok=True)
|
||||
if not basename.endswith(".jpg"):
|
||||
basename = basename + ".jpg"
|
||||
cv2.imwrite(osp.join(output_folder, basename + ".jpg"), img, [cv2.IMWRITE_JPEG_QUALITY, self.opt['compression_level']])
|
||||
return None
|
||||
|
||||
def __len__(self):
|
||||
|
|
Loading…
Reference in New Issue
Block a user