使用Matplotlib显示 plt.imshow(gray, cmap='gray') plt.title('Grayscale Image') plt.show() 保存处理后的图像 cv2.imwrite('example_gray.jpg', gray) 五、总结 在Python中保存图像的方式多种多样,选择合适的库和方法可以提高工作效率。Matplotlib适合用于生成
While working with images in Image Processing applications, quite often, you may need to store intermediate results of image transformations or save the final resulting image. When working with OpenCV Python, images are stored in NumPy ndarray. To save an image to the local file system, use cv...
这里的三个矩阵分别对应:灰度矩阵、通过mpimg.imsave+灰度矩阵存储为图像的矩阵、通过cv2.imwrite+灰度矩阵存储为图像的矩阵: 明显发现了三个矩阵,前两个格式为MN,最后一个是MN3。 最后补上两个导出图片信息对比,先是MN3的: 再是用opencv导出的M*N的: 图像在色彩上有一点点区别呢。然后我们看一看位深度就知道...
To save an image to a directory in Python using the Pillow library, first, import theImagemodule from Pillow and theosmodule. Open the image usingImage.open('image_name.jpg'), define your target directory, and ensure it exists usingos.makedirs(directory, exist_ok=True). Finally, save the ...
在上面的代码中,Image.new() 创建了一个新的图像对象,save_path 变量包含了图像的保存路径,最后调用 image.save(save_path) 将图像保存到指定路径。 使用OpenCV 库 虽然OpenCV 没有 save() 方法,但你可以使用 cv2.imwrite() 函数来保存图像。 python import cv2 import numpy as np # 创建一个新的图像对象...
grid_image = grid_image.numpy().transpose((1, 2, 0)) # 显示网格图像 plt.imshow(grid_image) plt.axis('off') # 不显示坐标轴 plt.show() 3、draw_bounding_boxes import cv2 import numpy as np # 读取一张图片 image = cv2.imread('your_image.jpg') ...
1.cv2.resize(image, (image_size, image_size), 0, 0, cv2.INTER_LINEAR) 参数说明:image表示输入图片,image_size表示变化后的图片大小,0, 0表示dx和dy, cv2.INTER_LINEAR表示插值的方式为线性插值
PIL.Image doesn't respect compress_level value and always output max 9 compressed images -> when optimize_image = True! So we turn that off for PNG TODO: test import cv2 / OpenCV:python-pillow/Pillow#5986-> not faster then PIL
waitKey(1) # 1 millisecond # Save results (image with detections) if save_img: if dataset.mode == 'image': cv2.imwrite(save_path, im0) else: # 'video' or 'stream' if vid_path != save_path: # new video vid_path = save_path if isinstance(vid_writer, cv2.VideoWriter): vid_...
Skipping the CV2/NumPy process entirely and using PIL alone, like this: with open(src_path, 'rb') as image_file: with Image.open(image_file) as img: img = img.convert('1') img.save(dst_path, format='tiff') Produces the same error, but with a different traceback: ...