Python cv2.COLOR_RGB2GRAY Examples
The following are 30
code examples of cv2.COLOR_RGB2GRAY().
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Example #1
| Source File: plate_locate.py From EasyPR-python with Apache License 2.0 | 8 votes |
|
def sobelOperT(self, img, blursize, morphW, morphH):
'''
No different with sobelOper ?
'''
blur = cv2.GaussianBlur(img, (blursize, blursize), 0, 0, cv2.BORDER_DEFAULT)
if len(blur.shape) == 3:
gray = cv2.cvtColor(blur, cv2.COLOR_RGB2GRAY)
else:
gray = blur
x = cv2.Sobel(gray, cv2.CV_16S, 1, 0, 3)
absX = cv2.convertScaleAbs(x)
grad = cv2.addWeighted(absX, 1, 0, 0, 0)
_, threshold = cv2.threshold(grad, 0, 255, cv2.THRESH_OTSU + cv2.THRESH_BINARY)
element = cv2.getStructuringElement(cv2.MORPH_RECT, (morphW, morphH))
threshold = cv2.morphologyEx(threshold, cv2.MORPH_CLOSE, element)
return threshold
Example #2
| Source File: object_detection_2d_photometric_ops.py From data_generator_object_detection_2d with GNU General Public License v3.0 | 7 votes |
|
def __call__(self, image, labels=None):
if self.current == 'RGB' and self.to == 'HSV':
image = cv2.cvtColor(image, cv2.COLOR_RGB2HSV)
elif self.current == 'RGB' and self.to == 'GRAY':
image = cv2.cvtColor(image, cv2.COLOR_RGB2GRAY)
if self.keep_3ch:
image = np.stack([image] * 3, axis=-1)
elif self.current == 'HSV' and self.to == 'RGB':
image = cv2.cvtColor(image, cv2.COLOR_HSV2RGB)
elif self.current == 'HSV' and self.to == 'GRAY':
image = cv2.cvtColor(image, cv2.COLOR_HSV2GRAY)
if self.keep_3ch:
image = np.stack([image] * 3, axis=-1)
if labels is None:
return image
else:
return image, labels
Example #3
| Source File: atari_wrapper.py From tf2rl with MIT License | 6 votes |
|
def observation(self, obs):
if self._key is None:
frame = obs
else:
frame = obs[self._key]
if self._grayscale:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(
frame, (self._width, self._height), interpolation=cv2.INTER_AREA
)
if self._grayscale:
frame = np.expand_dims(frame, -1)
if self._key is None:
obs = frame
else:
obs = obs.copy()
obs[self._key] = frame
return obs
Example #4
| Source File: rule_based.py From PythonPilot with Apache License 2.0 | 6 votes |
|
def __apply_canny(self, src, ksize=7, sigma=1.2, low_th=10, high_th=70):
"""Apply canny edge detection.
Args:
src (int): Input image BGR.
numpy.ndarray, (720, 1280, 3), 0~255
Returns:
dst (int): Output image.
numpy.ndarray, (720, 1280), 0~1
"""
gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY)
blur_gray = cv2.GaussianBlur(gray,(ksize, ksize), sigma)
dst = cv2.Canny(blur_gray, low_th, high_th) // 255
return dst
Example #5
| Source File: atari_wrappers.py From torchbeast with Apache License 2.0 | 6 votes |
|
def observation(self, obs):
if self._key is None:
frame = obs
else:
frame = obs[self._key]
if self._grayscale:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(
frame, (self._width, self._height), interpolation=cv2.INTER_AREA
)
if self._grayscale:
frame = np.expand_dims(frame, -1)
if self._key is None:
obs = frame
else:
obs = obs.copy()
obs[self._key] = frame
return obs
Example #6
| Source File: functional.py From torch-toolbox with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def adjust_saturation(img, saturation_factor):
"""Adjust color saturation of an image.
Args:
img (CV Image): CV Image to be adjusted.
saturation_factor (float): How much to adjust the saturation. 0 will
give a black and white image, 1 will give the original image while
2 will enhance the saturation by a factor of 2.
Returns:
CV Image: Saturation adjusted image.
"""
if not _is_numpy_image(img):
raise TypeError('img should be CV Image. Got {}'.format(type(img)))
im = img.astype(np.float32)
degenerate = cv2.cvtColor(
cv2.cvtColor(
im,
cv2.COLOR_RGB2GRAY),
cv2.COLOR_GRAY2RGB)
im = (1 - saturation_factor) * degenerate + saturation_factor * im
im = im.clip(min=0, max=255)
return im.astype(img.dtype)
Example #7
| Source File: functional.py From torch-toolbox with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def adjust_contrast(img, contrast_factor):
"""Adjust contrast of an Image.
Args:
img (CV Image): CV Image to be adjusted.
contrast_factor (float): How much to adjust the contrast. Can be any
non negative number. 0 gives a solid gray image, 1 gives the
original image while 2 increases the contrast by a factor of 2.
Returns:
CV Image: Contrast adjusted image.
"""
if not _is_numpy_image(img):
raise TypeError('img should be CV Image. Got {}'.format(type(img)))
im = img.astype(np.float32)
mean = round(cv2.cvtColor(im, cv2.COLOR_RGB2GRAY).mean())
im = (1 - contrast_factor) * mean + contrast_factor * im
im = im.clip(min=0, max=255)
return im.astype(img.dtype)
Example #8
| Source File: imgproc.py From dataflow with Apache License 2.0 | 6 votes |
|
def _augment(self, img, r):
old_dtype = img.dtype
if img.ndim == 3:
if self.rgb is not None:
m = cv2.COLOR_RGB2GRAY if self.rgb else cv2.COLOR_BGR2GRAY
grey = cv2.cvtColor(img.astype('float32'), m)
mean = np.mean(grey)
else:
mean = np.mean(img, axis=(0, 1), keepdims=True)
else:
mean = np.mean(img)
img = img * r + mean * (1 - r)
if self.clip or old_dtype == np.uint8:
img = np.clip(img, 0, 255)
return img.astype(old_dtype)
Example #9
| Source File: opencv_functional.py From deep-smoke-machine with BSD 3-Clause "New" or "Revised" License | 6 votes |
|
def to_grayscale(img, num_output_channels=1):
"""Convert image to grayscale version of image.
Args:
img (numpy ndarray): Image to be converted to grayscale.
Returns:
numpy ndarray: Grayscale version of the image.
if num_output_channels = 1 : returned image is single channel
if num_output_channels = 3 : returned image is 3 channel with r = g = b
"""
if not _is_numpy_image(img):
raise TypeError('img should be numpy ndarray. Got {}'.format(type(img)))
if num_output_channels==1:
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)[:,:,np.newaxis]
elif num_output_channels==3:
# much faster than doing cvtColor to go back to gray
img = np.broadcast_to(cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)[:,:,np.newaxis], img.shape)
return img
Example #10
| Source File: functional.py From opencv_transforms with MIT License | 6 votes |
|
def to_grayscale(img, num_output_channels=1):
"""Convert image to grayscale version of image.
Args:
img (numpy ndarray): Image to be converted to grayscale.
Returns:
numpy ndarray: Grayscale version of the image.
if num_output_channels = 1 : returned image is single channel
if num_output_channels = 3 : returned image is 3 channel with r = g = b
"""
if not _is_numpy_image(img):
raise TypeError('img should be numpy ndarray. Got {}'.format(type(img)))
if num_output_channels==1:
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)[:,:,np.newaxis]
elif num_output_channels==3:
# much faster than doing cvtColor to go back to gray
img = np.broadcast_to(cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)[:,:,np.newaxis], img.shape)
return img
Example #11
| Source File: CVFeatures.py From videofeatures with MIT License | 6 votes |
|
def computeFeatures(self, video):
descriptor_array = []
for i in range(video.shape[0]):
frame = cv2.cvtColor(video[i], cv2.COLOR_RGB2GRAY).astype('uint8')
_, descriptors = cv2.xfeatures2d.SURF_create().detectAndCompute(frame, None)
# make sure that descriptors have shape (n_descriptor, 64)
if descriptors is not None:
if descriptors.shape[0] < self.n_descriptors:
descriptors = np.concatenate([descriptors, np.zeros((self.n_descriptors - descriptors.shape[0], 64))],
axis=0)
else:
descriptors = descriptors[:self.n_descriptors]
else:
descriptors = np.zeros((self.n_descriptors, 64))
assert descriptors.shape == (self.n_descriptors, 64)
descriptor_array.append(descriptors)
return np.concatenate(descriptor_array, axis=0)
Example #12
| Source File: CVFeatures.py From videofeatures with MIT License | 6 votes |
|
def computeFeatures(self, video):
"""
todo: improve documentation
Computes SIFT features for a single video.
:param video: a video of shape (n_frames, width, height, channel)
:return: the features, shape ()
"""
descriptor_array = []
for i in range(video.shape[0]):
frame = cv2.cvtColor(video[i], cv2.COLOR_RGB2GRAY).astype('uint8')
_, descriptors = cv2.xfeatures2d.SIFT_create(nfeatures=self.n_descriptors).detectAndCompute(frame, None)
if descriptors is not None:
if descriptors.shape[0] < self.n_descriptors:
descriptors = np.concatenate([descriptors, np.zeros((self.n_descriptors - descriptors.shape[0], 128))], axis=0)
else:
descriptors = descriptors[:self.n_descriptors]
else:
descriptors = np.zeros((self.n_descriptors, 128))
assert descriptors.shape == (self.n_descriptors, 128)
descriptor_array.append(descriptors)
features = np.concatenate(descriptor_array, axis=0)
return features
Example #13
| Source File: dataset_scene.py From Decoupled-attention-network with MIT License | 6 votes |
|
def keepratio_resize(self, img):
cur_ratio = img.size[0] / float(img.size[1])
mask_height = self.img_height
mask_width = self.img_width
img = np.array(img)
if len(img.shape) == 3:
img = cv2.cvtColor(img, cv2.COLOR_RGB2GRAY)
if cur_ratio > self.target_ratio:
cur_target_height = self.img_height
cur_target_width = self.img_width
else:
cur_target_height = self.img_height
cur_target_width = int(self.img_height * cur_ratio)
img = cv2.resize(img, (cur_target_width, cur_target_height))
start_x = int((mask_height - img.shape[0])/2)
start_y = int((mask_width - img.shape[1])/2)
mask = np.zeros([mask_height, mask_width]).astype(np.uint8)
mask[start_x : start_x + img.shape[0], start_y : start_y + img.shape[1]] = img
img = mask
return img
Example #14
| Source File: dqn_atari.py From cleanrl with MIT License | 6 votes |
|
def observation(self, obs):
if self._key is None:
frame = obs
else:
frame = obs[self._key]
if self._grayscale:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(
frame, (self._width, self._height), interpolation=cv2.INTER_AREA
)
if self._grayscale:
frame = np.expand_dims(frame, -1)
if self._key is None:
obs = frame
else:
obs = obs.copy()
obs[self._key] = frame
return obs
Example #15
| Source File: device.py From fitch with MIT License | 5 votes |
|
def screen_shot_to_object(self) -> np.ndarray:
""" screen shot and return numpy array (data saved in memory) """
pic_path = self.screen_shot()
# temp file will be automatically removed after usage
data = cv2.imread(pic_path, cv2.COLOR_RGB2GRAY)
os.remove(pic_path)
return data
Example #16
| Source File: agc_demos.py From ICML2019-TREX with MIT License | 5 votes |
|
def GrayScaleWarpImage(image):
"""Warp frames to 84x84 as done in the Nature paper and later work."""
width=84
height=84
frame = cv2.cvtColor(image, cv2.COLOR_BGR2RGB)
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(frame, (width, height), interpolation=cv2.INTER_AREA)
#frame = np.expand_dims(frame, -1)
return frame
Example #17
| Source File: env.py From Street-fighter-A3C-ICM-pytorch with MIT License | 5 votes |
|
def process_frame(frame):
if frame is not None:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(frame, (168, 168))[None, :, :] / 255.
return frame
else:
return np.zeros((1, 168, 168))
Example #18
| Source File: atari_wrappers.py From ICML2019-TREX with MIT License | 5 votes |
|
def observation(self, frame):
if self.grayscale:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(frame, (self.width, self.height), interpolation=cv2.INTER_AREA)
if self.grayscale:
frame = np.expand_dims(frame, -1)
return frame
Example #19
| Source File: atari_wrappers.py From ICML2019-TREX with MIT License | 5 votes |
|
def observation(self, frame):
if self.grayscale:
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(frame, (self.width, self.height), interpolation=cv2.INTER_AREA)
if self.grayscale:
frame = np.expand_dims(frame, -1)
return frame
Example #20
| Source File: utils.py From Deep-Q-Learning-Paper-To-Code with MIT License | 5 votes |
|
def observation(self, obs):
new_frame = cv2.cvtColor(obs, cv2.COLOR_RGB2GRAY)
resized_screen = cv2.resize(new_frame, self.shape[1:],
interpolation=cv2.INTER_AREA)
new_obs = np.array(resized_screen, dtype=np.uint8).reshape(self.shape)
new_obs = np.swapaxes(new_obs, 2,0)
new_obs = new_obs / 255.0
return new_obs
Example #21
| Source File: utils.py From Deep-Q-Learning-Paper-To-Code with MIT License | 5 votes |
|
def observation(self, obs):
new_frame = cv2.cvtColor(obs, cv2.COLOR_RGB2GRAY)
resized_screen = cv2.resize(new_frame, self.shape[1:],
interpolation=cv2.INTER_AREA)
new_obs = np.array(resized_screen, dtype=np.uint8).reshape(self.shape)
new_obs = np.swapaxes(new_obs, 2,0)
new_obs = new_obs / 255.0
return new_obs
Example #22
| Source File: rule_based.py From PythonPilot with Apache License 2.0 | 5 votes |
|
def __apply_multi_threshold(self, src):
"""Apply multi thresholding using LAB, HLS and HSV.
Args:
src (int): Input image BGR.
numpy.ndarray, (720, 1280, 3), 0~255
Returns:
dst (int): Output image.
numpy.ndarray, (720, 1280), 0~1
"""
settings = []
settings.append({'cspace': 'LAB', 'channel': 2, 'clipLimit': 2.0, 'threshold': 190})
settings.append({'cspace': 'HLS', 'channel': 1, 'clipLimit': 1.0, 'threshold': 200})
settings.append({'cspace': 'HSV', 'channel': 2, 'clipLimit': 3.0, 'threshold': 230})
gray = cv2.cvtColor(src, cv2.COLOR_RGB2GRAY)
dst = np.zeros_like(gray)
for s in settings:
color_t = getattr(cv2, 'COLOR_RGB2{}'.format(s['cspace']))
gray = cv2.cvtColor(src, color_t)[:,:,s['channel']]
clahe = cv2.createCLAHE(s['clipLimit'], tileGridSize=(8,8))
norm_img = clahe.apply(gray)
binary = np.zeros_like(norm_img)
binary[(norm_img >= s['threshold']) & (norm_img <= 255)] = 1
dst[(dst == 1) | (binary == 1)] = 1
return dst
Example #23
| Source File: utils.py From Deep-Q-Learning-Paper-To-Code with MIT License | 5 votes |
|
def observation(self, obs):
new_frame = cv2.cvtColor(obs, cv2.COLOR_RGB2GRAY)
resized_screen = cv2.resize(new_frame, self.shape[1:],
interpolation=cv2.INTER_AREA)
new_obs = np.array(resized_screen, dtype=np.uint8).reshape(self.shape)
new_obs = np.swapaxes(new_obs, 2,0)
new_obs = new_obs / 255.0
return new_obs
Example #24
| Source File: utils.py From Deep-Q-Learning-Paper-To-Code with MIT License | 5 votes |
|
def observation(self, obs):
new_frame = cv2.cvtColor(obs, cv2.COLOR_RGB2GRAY)
resized_screen = cv2.resize(new_frame, self.shape[1:],
interpolation=cv2.INTER_AREA)
new_obs = np.array(resized_screen, dtype=np.uint8).reshape(self.shape)
new_obs = new_obs / 255.0
return new_obs
Example #25
| Source File: utils.py From Deep-Q-Learning-Paper-To-Code with MIT License | 5 votes |
|
def observation(self, obs):
new_frame = cv2.cvtColor(obs, cv2.COLOR_RGB2GRAY)
resized_screen = cv2.resize(new_frame, self.shape[1:],
interpolation=cv2.INTER_AREA)
new_obs = np.array(resized_screen, dtype=np.uint8).reshape(self.shape)
new_obs = new_obs / 255.0
return new_obs
Example #26
| Source File: datagen.py From Convolutional-Pose-Machine-tf with GNU Lesser General Public License v3.0 | 5 votes |
|
def test(self, toWait=0.2):
""" TESTING METHOD
You can run it to see if the preprocessing is well done.
Wait few seconds for loading, then diaporama appears with image and highlighted joints
/!\ Use Esc to quit
Args:
toWait : In sec, time between pictures
"""
self._create_train_table()
self._create_sets()
for i in range(len(self.train_set)):
img = self.open_img(self.train_set[i])
w = self.data_dict[self.train_set[i]]['weights']
padd, box = self._crop_data(img.shape[0], img.shape[1], self.data_dict[self.train_set[i]]['box'],
self.data_dict[self.train_set[i]]['joints'], boxp=0.0)
new_j = self._relative_joints(box, padd, self.data_dict[self.train_set[i]]['joints'], to_size=self.in_size)
rhm = self._generate_hm(self.in_size, self.in_size, new_j, self.in_size, w)
rimg = self._crop_img(img, padd, box)
# See Error in self._generator
# rimg = cv2.resize(rimg, (self.in_size,self.in_size))
rimg = scm.imresize(rimg, (self.in_size, self.in_size))
# rhm = np.zeros((self.in_size,self.in_size,16))
# for i in range(16):
# rhm[:,:,i] = cv2.resize(rHM[:,:,i], (self.in_size,self.in_size))
grimg = cv2.cvtColor(rimg, cv2.COLOR_RGB2GRAY)
cv2.imshow('image', grimg / 255 + np.sum(rhm, axis=2))
# Wait
time.sleep(toWait)
if cv2.waitKey(1) == 27:
print('Ended')
cv2.destroyAllWindows()
break
# ------------------------------- PCK METHODS-------------------------------
Example #27
| Source File: toolbox.py From stagesepx with MIT License | 5 votes |
|
def turn_grey(old: np.ndarray) -> np.ndarray:
try:
return cv2.cvtColor(old, cv2.COLOR_RGB2GRAY)
except cv2.error:
return old
Example #28
| Source File: toolbox.py From findit with MIT License | 5 votes |
|
def turn_grey(old: np.ndarray) -> np.ndarray:
try:
return cv2.cvtColor(old, cv2.COLOR_RGB2GRAY)
except cv2.error:
return old
Example #29
| Source File: visual_augmentation.py From face_landmark with Apache License 2.0 | 5 votes |
|
def gray(src):
g_img=cv2.cvtColor(src,cv2.COLOR_RGB2GRAY)
src[:,:,0]=g_img
src[:,:,1]=g_img
src[:,:,2]=g_img
return src
Example #30
| Source File: atari_wrappers_deprecated.py From learning2run with MIT License | 5 votes |
|
def process(frame):
frame = cv2.cvtColor(frame, cv2.COLOR_RGB2GRAY)
frame = cv2.resize(frame, (84, 84), interpolation=cv2.INTER_AREA)
return frame.reshape(84, 84, 1)
