def cvts(root, fm1='dng', fm2='jpg', num_worker=3):
dir1, dir2 = osp.join(root, fm1), osp.join(root, fm2)
ls1 = os.listdir(dir1)
mkdir(dir2)
outputs = bj(dir2, be(ls1, fm2))
inputs = bj(dir1, ls1)
with Pool(num_worker) as p:
p.starmap_async(convert, zip(inputs, outputs))
def bcrop2(root, in_dir='jpg16', out_dir="jpg16c"):
in_dir, out_dir = osp.join(root, in_dir), osp.join(root, out_dir)
ls = os.listdir(in_dir)
if not os.path.exists(out_dir):
os.makedirs(out_dir)
inputs = bj(in_dir, ls)
outputs = bj(out_dir, ls)
with Pool(16, initialize_bds, (root, )) as p:
p.starmap_async(crop, zip(inputs, outputs))
def check_shape(root,fm1='jpgc',fm2='pngc'):
dir1,dir2=osp.join(root,fm1),osp.join(root,fm2)
ls1,ls2=bj(dir1,sorted(os.listdir(dir1))),bj(dir2,sorted(os.listdir(dir2)))
for f1,f2 in zip(ls1,ls2):
im1=imread(f1)
im2=imread(f2)
print(im2.max(),end='\r')
if im1.shape[:2] != im2.shape[:2]:
print(im1.shape,im2.shape)
return
def tbnails(root, in_dir='jpg', out_dir='jpg16'):
in_dir, out_dir = osp.join(root, in_dir), osp.join(root, out_dir)
ls = os.listdir(in_dir)
if not os.path.exists(out_dir):
os.makedirs(out_dir)
inputs = bj(in_dir, ls)
outputs = bj(out_dir, ls)
with Pool(3) as p:
p.starmap_async(scale, zip(inputs, outputs))
def get_bb(root):
df = get_trip(root)
gts = pd.unique(df["gt"].map(lambda x: x + '.jpg'))
inputs = bj(osp.join(root, 'jpg16'), gts)
bbs = []
for i in inputs:
img = imageio.imread(i)
h, w, _ = img.shape
plt.imshow(img)
plt.draw()
# plt.imshow(img)
pts = plt.ginput(2)
print(pts)
if len(pts) < 2:
break
(x0, y0), (x1, y1) = pts
bbs.append([y0 / h, y1 / h, x0 / w, x1 / w])
bbs = np.array(bbs)
print(bbs)
bb = [
np.max(bbs[:, 0]),
np.min(bbs[:, 1]),
np.max(bbs[:, 2]),
np.min(bbs[:, 3])
]
print(bb)
with open(osp.join(root, 'bb.csv'), 'a') as f:
f.write(','.join([str(b) for b in bb]))
def batch_rotate(root, fm1='png', num_worker=16):
dir1 = osp.join(root, fm1)
ls1 = os.listdir(dir1)
inputs = bj(dir1, ls1)
with Pool(num_worker) as p:
p.map(inplace_rotate, inputs)