def test_uint8_image(self):
'''
Tests that uint8 image (pixel values in [0, 255]) is not changed
'''
test_image = np.random.randint(0, 256, size=(3, 32, 32), dtype=np.uint8)
scale_factor = summary._calc_scale_factor(test_image)
assert scale_factor == 1, 'Values are already in [0, 255], scale factor should be 1'
def make_gif(image_seq, fps=4, print_filepath=False, filename=None, filedir=None):
#print(debug_sample_tuple[0].shape)
idx_dict = {
'orig_depth': 0
}
# if len(debug_sample_tuple[idx_dict['orig_depth']].shape) == 3:
# print("CHANGING TxWxH => 1xTx1XWxH")
# https://github.com/lanpa/tensorboardX/blob/master/tensorboardX/summary.py
#tensor = imag
tensor = image_seq
if len(tensor.shape) == 3:
C = 1
T, H, W = tensor.shape
elif len(tensor.shape) == 4:
T, C, H, W = tensor.shape
tensor = tensor.reshape(1, T, C, H, W) # prepare video requires this format
tensor = _prepare_video(tensor)
scale_factor = _calc_scale_factor(tensor)
tensor = tensor.astype(np.float32)
tensor = (tensor * scale_factor).astype(np.uint8)
#print(tensor)
#t, h, w, c = tensor.shape
clip = mpy.ImageSequenceClip(list(tensor), fps=fps)
if filename is None:
filename = tempfile.NamedTemporaryFile(suffix='.gif', delete=False, dir=filedir).name
clip.write_gif(filename, verbose=False, progress_bar=False)
if print_filepath:
print("GIF Path:", filename)
return filename
def test_float32_image(self):
'''
Tests that float32 image (pixel values in [0, 1]) are scaled correctly
to [0, 255]
'''
test_image = np.random.rand(3, 32, 32).astype(np.float32)
scale_factor = summary._calc_scale_factor(test_image)
assert scale_factor == 255, 'Values are in [0, 1], scale factor should be 255'
def test_float32_image(self):
'''
Tests that float32 image (pixel values in [0, 1]) are scaled correctly
to [0, 255]
'''
test_image = tensor_N(shape=(3, 32, 32))
scale_factor = summary._calc_scale_factor(test_image)
assert scale_factor == 255, 'Values are in [0, 1], scale factor should be 255'
