importnumpyasnpimportmatplotlib.pyplotaspltfromPILimportImage# 1. 读取灰度图像gray_img=Image.open('gray_image.png').convert('L')gray_array=np.array(gray_img)# 2. 创建空的彩色图像数组height,width=gray_array.shape color_im
然后,使用以下代码将RGB图像转换为numpy数组: 代码语言:python 代码运行次数:0 复制Cloud Studio 代码运行 from PIL import Image import numpy as np # 读取图像文件并将其转换为numpy数组 def image_to_numpy_array(image_path): image = Image.open(image_path) return np.array(image) # 示例:将图像转换为...
M_blue = Image.fromarray(RGB_image(reduced_M, 'B')) display(M_blue) 6、应用滤镜 这里使用棕褐色(Sepia)作为示例,可以根据不同的要求修改转换矩阵 def apply_sepia(image): # Sepia transformation matrix sepia_matrix = np.array([[0.393, 0.769, 0.189], [0.349, 0.686, 0.168], [0.272, 0.534,...
M_blue = Image.fromarray(RGB_image(reduced_M, 'B')) display(M_blue) 6、应用滤镜 这里使用棕褐色(Sepia)作为示例,可以根据不同的要求修改转换矩阵 代码语言:javascript 代码运行次数:0 运行 AI代码解释 def apply_sepia(image): # Sepia transformation matrix sepia_matrix = np.array([[0.393, 0.769,...
# Extract the focused part using array slicing focused_part = image[top:bottom, left:right] return focused_part display(crop_image(reduced_M, 4, 2)) 5、RGB通道 def RGB_image(image,image_color): if image_color == 'R': #make a copy of image for the color channel ...
#Use PIL to access image data from PIL import Image img = Image.open('monalisa.jpg') #Create array from image data M = np.array(img) #Display array from image data display(Image.fromarray(M)) 1. 2. 3. 4. 5. 6. 7. 8. ...
M_blue = Image.fromarray(RGB_image(reduced_M,'B'))display(M_blue) 6、应用滤镜 这里使用棕褐色(Sepia)作为示例,可以根据不同的要求修改转换矩阵 def apply_sepia(image): # Sepia transformationmatrixsepia_matrix =np.array([[0.393,0.769,0.189], ...
In particular, OpenCV in-place operations require a contiguous array from Python to avoid unexpected results. The safest approach is to always make a copy of the array as in the examples below. Examples Note to use .copy() to avoid unexpected results if using OpenCV. If just using ...
# 读取图像并转换为 RGB 模式image=Image.open('path/to/your/image.jpg').convert('RGB')# 将图像转换为 NumPy 数组image_array=np.array(image)# 将图像变为NumPy数组 1. 2. 3. 4. 注意:请将'path/to/your/image.jpg'替换为您的图像文件路径。后的.convert('RGB')是为了确保图像在 RGB 模式下。
importnumpyasnp# 创建不同数据类型的数组arr1=np.array([[1,2,3]],dtype=np.int32)arr2=np.array([[4.5,5.5,6.5]],dtype=np.float64)# 垂直拼接这些数组result=np.concatenate((arr1,arr2),axis=0)print("numpyarray.com - Vertically concatenated arrays with different dtypes:")print(result)print...