我有一個實作 PixelRL 的問題。PixelRL github。我想使用 int16 ( -32768 ~ 32767 ) 讀取影像并將其保存為原始資料。但我不知道如何讓 cv2.imwrite() 支持它。使用 p = (p[0]*65535 0.5).astype(np.int16) 時，保存 8bit 影像。有沒有辦法將影像寫入 int16 和原始資料？
謝謝你。
class MiniBatchLoader(object):
def __init__(self, train_path, test_path, image_dir_path, crop_size):
# load data paths
self.training_path_infos = self.read_paths(train_path, image_dir_path)
self.testing_path_infos = self.read_paths(test_path, image_dir_path)
self.crop_size = crop_size
# test ok
@staticmethod
def path_label_generator(txt_path, src_path):
for line in open(txt_path):
line = line.strip()
src_full_path = os.path.join(src_path, line)
if os.path.isfile(src_full_path):
yield src_full_path
# test ok
@staticmethod
def count_paths(path):
c = 0
for _ in open(path):
c = 1
return c
# test ok
@staticmethod
def read_paths(txt_path, src_path):
cs = []
for pair in MiniBatchLoader.path_label_generator(txt_path, src_path):
cs.append(pair)
return cs
def load_training_data(self, indices):
return self.load_data(self.training_path_infos, indices, augment=True)
def load_testing_data(self, indices):
return self.load_data(self.testing_path_infos, indices)
# test ok
def load_data(self, path_infos, indices, augment=False):
mini_batch_size = len(indices)
in_channels = 1
if augment:
xs = np.zeros((mini_batch_size, in_channels, self.crop_size, self.crop_size)).astype(np.float32)
for i, index in enumerate(indices):
path = path_infos[index]
img = cv2.imread(path,0)
if img is None:
raise RuntimeError("invalid image: {i}".format(i=path))
h, w = img.shape
if np.random.rand() > 0.5:
img = np.fliplr(img)
if np.random.rand() > 0.5:
angle = 10*np.random.rand()
if np.random.rand() > 0.5:
angle *= -1
M = cv2.getRotationMatrix2D((w/2,h/2),angle,1)
img = cv2.warpAffine(img,M,(w,h))
rand_range_h = h-self.crop_size
rand_range_w = w-self.crop_size
x_offset = np.random.randint(rand_range_w)
y_offset = np.random.randint(rand_range_h)
img = img[y_offset:y_offset self.crop_size, x_offset:x_offset self.crop_size]
xs[i, 0, :, :] = (img/255).astype(np.float32)
elif mini_batch_size == 0:
for i, index in enumerate(indices):
path = path_infos[index]
img = cv2.imread(path,0)
if img is None:
raise RuntimeError("invalid image: {i}".format(i=path))
h, w = img.shape
xs = np.zeros((mini_batch_size, in_channels, h, w)).astype(np.float16)
xs[0, 0, :, :] = (img/255).astype(np.float16)
else:
raise RuntimeError("mini batch size must be 1 when testing")
return xs
def test(loader, agent, fout):
sum_psnr = 0
sum_reward = 0
test_data_size = MiniBatchLoader.count_paths(TESTING_DATA_PATH)
current_state = State.State((TEST_BATCH_SIZE,1,CROP_SIZE,CROP_SIZE), MOVE_RANGE)
for i in range(0, test_data_size, TEST_BATCH_SIZE):
raw_x = loader.load_testing_data(np.array(range(i, i TEST_BATCH_SIZE)))
raw_n = np.random.normal(MEAN,SIGMA,raw_x.shape).astype(raw_x.dtype)/255
current_state.reset(raw_x,raw_n)
reward = cp.zeros(raw_x.shape, raw_x.dtype)*255
for t in range(0, EPISODE_LEN):
previous_image = current_state.image.copy()
action, inner_state = agent.act(current_state.tensor)
current_state.step(action, inner_state)
reward = np.square(raw_x - previous_image)*255 - np.square(raw_x - current_state.image)*255
sum_reward = cp.mean(reward)*cp.power(GAMMA,t)
agent.stop_episode()
p = np.maximum(0,current_state.image)
p = np.minimum(1,p)
p = (p[0]*65535 0.5).astype(np.int16)
p = cp.transpose(p,(1,2,0))
cv2.imwrite(output_save_path '/' str(i) '.tiff',p)
uj5u.com熱心網友回復：
有沒有辦法...？
不。
https://docs.opencv.org/3.4/d4/da8/group__imgcodecs.html#gabbc7ef1aa2edfaa87772f1202d67e0ce
一般來說，使用此功能只能保存 8 位單通道或 3 通道 ... 影像，但以下情況除外：
- 可以保存 16 位無符號 (CV_16U) 影像...
您可能希望將已簽名的 16 位值轉換為 CV_16U 格式。
或者，您可以考慮撰寫 32 位影像，然后呼叫后處理程式將它們縮小為您喜歡的 16 位格式。
轉載請註明出處，本文鏈接：https://www.uj5u.com/gongcheng/472817.html