def __getitem__(self, index):
index = index % self.size
img1 = frame_utils.read_gen(self.image_list[index][0])
img2 = frame_utils.read_gen(self.image_list[index][1])
flow = frame_utils.read_gen(self.flow_list[index])
images = [img1, img2]
image_size = img1.shape[:2]
if self.is_cropped:
cropper = StaticRandomCrop(image_size, self.crop_size)
else:
cropper = StaticCenterCrop(image_size, self.render_size)
images = list(map(cropper, images))
flow = cropper(flow)
images = np.array(images).transpose(3, 0, 1, 2)
flow = flow.transpose(2, 0, 1)
images = torch.from_numpy(images.astype(np.float32))
flow = torch.from_numpy(flow.astype(np.float32))
return [images], [flow]
def __init__(self,
args,
is_cropped,
root="/path/to/frames/only/folder",
iext="png",
replicates=1):
self.args = args
self.is_cropped = is_cropped
self.crop_size = args.crop_size
self.render_size = args.inference_size
self.replicates = replicates
images = sorted(glob(join(root, "*." + iext)))
self.image_list = []
for i in range(len(images) - 1):
im1 = images[i]
im2 = images[i + 1]
self.image_list += [[im1, im2]]
self.size = len(self.image_list)
self.frame_size = frame_utils.read_gen(self.image_list[0][0]).shape
if ((self.render_size[0] < 0) or (self.render_size[1] < 0)
or (self.frame_size[0] % 64) or (self.frame_size[1] % 64)):
self.render_size[0] = ((self.frame_size[0]) // 64) * 64
self.render_size[1] = ((self.frame_size[1]) // 64) * 64
args.inference_size = self.render_size
def __init__(self,
args,
is_cropped,
root="/path/to/FlyingChairs_release/data",
replicates=1):
self.args = args
self.is_cropped = is_cropped
self.crop_size = args.crop_size
self.render_size = args.inference_size
self.replicates = replicates
images = sorted(glob(join(root, "*.ppm")))
self.flow_list = sorted(glob(join(root, "*.flo")))
assert len(images) // 2 == len(self.flow_list)
self.image_list = []
for i in range(len(self.flow_list)):
im1 = images[2 * i]
im2 = images[2 * i + 1]
self.image_list += [[im1, im2]]
assert len(self.image_list) == len(self.flow_list)
self.size = len(self.image_list)
self.frame_size = frame_utils.read_gen(self.image_list[0][0]).shape
if ((self.render_size[0] < 0) or (self.render_size[1] < 0)
or (self.frame_size[0] % 64) or (self.frame_size[1] % 64)):
self.render_size[0] = ((self.frame_size[0]) // 64) * 64
self.render_size[1] = ((self.frame_size[1]) // 64) * 64
args.inference_size = self.render_size
def __init__(self,
args,
is_cropped=False,
root="",
dstype="clean",
replicates=1):
self.args = args
self.is_cropped = is_cropped
self.crop_size = args.crop_size
self.render_size = args.inference_size
self.replicates = replicates
flow_root = join(root, "flow")
image_root = join(root, dstype)
file_list = sorted(glob(join(flow_root, "*/*.flo")))
self.flow_list = []
self.image_list = []
for file in file_list:
if "test" in file:
# print file
continue
fbase = file[len(flow_root) + 1:]
fprefix = fbase[:-8]
fnum = int(fbase[-8:-4])
img1 = join(image_root, fprefix + "%04d" % (fnum + 0) + ".png")
img2 = join(image_root, fprefix + "%04d" % (fnum + 1) + ".png")
if not isfile(img1) or not isfile(img2) or not isfile(file):
continue
self.image_list += [[img1, img2]]
self.flow_list += [file]
self.size = len(self.image_list)
self.frame_size = frame_utils.read_gen(self.image_list[0][0]).shape
if ((self.render_size[0] < 0) or (self.render_size[1] < 0)
or (self.frame_size[0] % 64) or (self.frame_size[1] % 64)):
self.render_size[0] = ((self.frame_size[0]) // 64) * 64
self.render_size[1] = ((self.frame_size[1]) // 64) * 64
args.inference_size = self.render_size
assert len(self.image_list) == len(self.flow_list)
def __init__(self,
args,
is_cropped,
root="/path/to/flyingthings3d",
dstype="frames_cleanpass",
replicates=1):
self.args = args
self.is_cropped = is_cropped
self.crop_size = args.crop_size
self.render_size = args.inference_size
self.replicates = replicates
image_dirs = sorted(glob(join(root, dstype, "TRAIN/*/*")))
image_dirs = sorted([join(f, "left") for f in image_dirs] +
[join(f, "right") for f in image_dirs])
flow_dirs = sorted(
glob(join(root, "optical_flow_flo_format/TRAIN/*/*")))
flow_dirs = sorted([join(f, "into_future/left") for f in flow_dirs] +
[join(f, "into_future/right") for f in flow_dirs])
assert len(image_dirs) == len(flow_dirs)
self.image_list = []
self.flow_list = []
for idir, fdir in zip(image_dirs, flow_dirs):
images = sorted(glob(join(idir, "*.png")))
flows = sorted(glob(join(fdir, "*.flo")))
for i in range(len(flows)):
self.image_list += [[images[i], images[i + 1]]]
self.flow_list += [flows[i]]
assert len(self.image_list) == len(self.flow_list)
self.size = len(self.image_list)
self.frame_size = frame_utils.read_gen(self.image_list[0][0]).shape
if ((self.render_size[0] < 0) or (self.render_size[1] < 0)
or (self.frame_size[0] % 64) or (self.frame_size[1] % 64)):
self.render_size[0] = ((self.frame_size[0]) // 64) * 64
self.render_size[1] = ((self.frame_size[1]) // 64) * 64
args.inference_size = self.render_size
def __init__(self,
args,
is_cropped,
root="/path/to/chairssdhom/data",
dstype="train",
replicates=1):
self.args = args
self.is_cropped = is_cropped
self.crop_size = args.crop_size
self.render_size = args.inference_size
self.replicates = replicates
image1 = sorted(glob(join(root, dstype, "t0/*.png")))
image2 = sorted(glob(join(root, dstype, "t1/*.png")))
self.flow_list = sorted(glob(join(root, dstype, "flow/*.flo")))
assert len(image1) == len(self.flow_list)
self.image_list = []
for i in range(len(self.flow_list)):
im1 = image1[i]
im2 = image2[i]
self.image_list += [[im1, im2]]
assert len(self.image_list) == len(self.flow_list)
self.size = len(self.image_list)
self.frame_size = frame_utils.read_gen(self.image_list[0][0]).shape
if ((self.render_size[0] < 0) or (self.render_size[1] < 0)
or (self.frame_size[0] % 64) or (self.frame_size[1] % 64)):
self.render_size[0] = ((self.frame_size[0]) // 64) * 64
self.render_size[1] = ((self.frame_size[1]) // 64) * 64
args.inference_size = self.render_size