| into an image, but still retain the original. | | :rtype: :py:class:`~PIL.Image.Image` | :returns: An :py:class:`~PIL.Image.Image` object. | | crop(self, box=None) | Returns a rectangular region from this image. The box is a | 4-tuple defining the left, upper, right, ...
合成Image.blend(i1,i2,a)/Image.composite(i1,i2,mask) 缩略图 thumbnail(size,filter=None) Modifies in-place,Preserves aspect ratio >>> myImage.thumbnail ((128, 128), Image.ANTIALIAS) 剪切crop(bbox) >>> bounds = (100, 100, 400, 400) >>> cutoutIm = myImage.crop (bounds) 粘贴pa...
张量的PIL图像_crop是指在TensorFlow中使用Python Imaging Library(PIL)进行图像裁剪操作的过程。 图像裁剪是指从原始图像中截取出感兴趣的部分,通常用于图像预处理、数据增强和区域兴趣检测等任务。在TensorFlow中,可以使用PIL库提供的crop()函数来实现图像裁剪操作。 PIL库是一个强大的图像处理库,提供了丰富的图像处理...
im.crop(box) ⇒ image Returns a copy of a rectangular region from the current image. The box is a 4-tuple defining the left, upper, right, and lower pixel coordinate. This is a lazy operation. Changes to the source image may or may not be reflected in the cropped image. To get a...
...当从一个颜色图像转换为黑白图像时,PIL库使用ITU-R601-2 luma转换公式: L = R * 299/1000 + G * 587/1000 + B * 114/1000 当转换为2位图像(模式...(高) im_crop = im1.crop(box) im_crop.save("he.jpg") 4、Draft 定义:im.draft(mode,size) 含义:配置图像文件加载器,使得返回一个...
合成Image.blend(i1,i2,a)/Image.composite(i1,i2,mask) 缩略图 thumbnail(size,filter=None) Modifies in-place,Preserves aspect ratio >>> myImage.thumbnail ((128, 128), Image.ANTIALIAS) 剪切crop(bbox) >>> bounds = (100, 100, 400, 400) ...
合成Image.blend(i1,i2,a)/Image.composite(i1,i2,mask) 缩略图 thumbnail(size,filter=None) Modifies in-place,Preserves aspect ratio >>> myImage.thumbnail ((128, 128), Image.ANTIALIAS) 剪切crop(bbox) >>> bounds = (100, 100, 400, 400) ...
ImageChops.composite(image1, image2, mask) ⇒ image Same as the composite function in the Image module. 一样的复合函数在图像模块。 offset(抵消) ImageChops.offset(image, xoffset, yoffset) ⇒ image ImageChops.offset(image, offset) ⇒ image Returns a copy of the image where data has be...
(self,image,boundingBox): #take bounding box, draw an oval on the image, save boundingBox locally self.box = boundingBox self.avgInt = 0 self.draw = ImageDraw.Draw(image) self.draw.rectangle(boundingBox,outline='white') def capture(self): region_to_capture = image.crop(box) region_...
crop(self, box=None) Crop region from image draft(self, mode, size) Configure image decoder filter(self, filter) Apply environment filter to image fromstring(self, data, decoder_name='raw', *args) Load data to image from binary string ...