我有一个任务需要转换RGB到YIQ和回来只使用简单的函数(在lib:plt cv2 np)
我得到的是“天真”的代码解决方案:
def transformRGB2YIQ(imgRGB: np.ndarray) -> np.ndarray:
"""
Converts an RGB image to YIQ color space
:param imgRGB: An Image in RGB
:return: A YIQ in image color space
"""
yiq_from_rgb = np.array([[0.299, 0.587, 0.114],
[0.59590059, -0.27455667, -0.32134392],
[0.21153661, -0.52273617, 0.31119955]])
YIQ = np.dot(imgRGB.reshape(-1, 3), yiq_from_rgb).reshape(imgRGB.shape)
return YIQ
pass
def transformYIQ2RGB(imgYIQ: np.ndarray) -> np.ndarray:
"""
Converts an YIQ image to RGB color space
:param imgYIQ: An Image in YIQ
:return: A RGB in image color space
"""
yiq_from_rgb = np.array([[0.299, 0.587, 0.114],
[0.59590059, -0.27455667, -0.32134392],
[0.21153661, -0.52273617, 0.31119955]])
rgb_from_yiq = np.linalg.inv(yiq_from_rgb)
RGB = np.dot(imgYIQ.reshape(-1, 3), rgb_from_yiq).reshape(imgYIQ.shape)
return RGB
pass
字符串
我尝试使用np.dot并重新塑造img,以便我可以将其乘以矩阵,就像这样:
的数据
但运气不好,我答错了
还尝试:
def transformRGB2YIQ(imgRGB: np.ndarray) -> np.ndarray:
"""
Converts an RGB image to YIQ color space
:param imgRGB: An Image in RGB
:return: A YIQ in image color space
"""
YIQ = np.ndarray(imgRGB.shape)
YIQ[:, :, 0] = 0.299 * imgRGB[:, :, 0] + 0.587 * imgRGB[:, :, 1] + 0.114 * imgRGB[:, :, 2]
YIQ[:, :, 1] = 0.59590059 * imgRGB[:, :, 0] + (-0.27455667) * imgRGB[:, :, 1] + (-0.32134392) * imgRGB[:, :, 2]
YIQ[:, :, 2] = 0.21153661 * imgRGB[:, :, 0] + (-0.52273617) * imgRGB[:, :, 1] + 0.31119955 * imgRGB[:, :, 2]
return YIQ
pass
def transformYIQ2RGB(imgYIQ: np.ndarray) -> np.ndarray:
"""
Converts an YIQ image to RGB color space
:param imgYIQ: An Image in YIQ
:return: A RGB in image color space
"""
yiq_from_rgb = np.array([[0.299, 0.587, 0.114],
[0.59590059, -0.27455667, -0.32134392],
[0.21153661, -0.52273617, 0.31119955]])
rgb_from_yiq = np.linalg.inv(yiq_from_rgb)
RGB = np.ndarray(imgYIQ.shape)
RGB[:, :, 0] = 1.00000001 * imgYIQ[:, :, 0] + 0.95598634 * imgYIQ[:, :, 1] + 0.6208248 * imgYIQ[:, :, 2]
RGB[:, :, 1] = 0.99999999 * imgYIQ[:, :, 0] + (-0.27201283) * imgYIQ[:, :, 1] + (-0.64720424) * imgYIQ[:, :, 2]
RGB[:, :, 2] = 1.00000002 * imgYIQ[:, :, 0] + (-1.10674021) * imgYIQ[:, :, 1] + 1.70423049 * imgYIQ[:, :, 2]
return RGB
pass
型
但这不是一个有效的答案在我的课上,任何想法的如何使它在一个单一的步骤?
2条答案
按热度按时间yhqotfr81#
经过多次尝试和错误,我找到了一个解决方案。
字符串
5w9g7ksd2#
我能够使用numpy的matmul从RGB转换为YIQ,它能够对图像的每个像素执行矩阵乘法。注意,我使用的是numpy 1.24.3。dot函数也可以工作,在这种情况下,它计算每个像素的和积。更多细节请参见文档。
第一个月
下面的代码有两个实现。
字符串