我有一个图像,它被裁剪并调整为图像输入大小。在我看来,这和仿射变换是一样的。
我试图简化下面的代码,所以它通过使用函数做同样的事情:(类似于下面的例子在最后)。
scipy.ndimage.affine_transform()
问题是我并不真正理解该函数的参数,因此我无法使用affine_transform()函数实现优雅的一行代码。提供和解释代码的解决方案可能有助于我更好地理解affine_transform()函数。
import numpy as npy
import PIL.Image
import scipy.misc as smc
import scipy.ndimage as snd
#crop factor
s = 1.045
#input image
img2crop = npy.float32(PIL.Image.open("input_image.jpg)")
h, w = img2crop.shape[:2] #get the dimensions of the input image
#Box-crop values: calculate new crop Dimensions based on 's'
wcrop = float(w) / (s)
hcrop = float(wcrop) / (float(w) / float(h))
hcrop = int(round(hcrop))
wcrop = int(round(wcrop))
#crop applied from top-left to right and bottom
b_left = 0
b_top = 0
b_width = wcrop
b_height = hcrop
b_box = (b_left, b_top, b_width, b_height)
#cropped region
region = img2crop.crop(b_box)
#resize cropped region back to input size
resized_region = smc.imresize(region, (h, w), interp='nearest', mode=None)
#save cropped and resized region as new file in output folder
PIL.Image.fromarray(np.uint8(resized_newregion)).save("output_image.jpg")
问题:上面做裁剪和调整大小的代码如何表示为仿射变换?
这个例子在四面均匀裁剪,居中
s = 0.0065
cropped_and_resized_image = snd.affine_transform(input_image.jpg, [1-s,1-s,1], [h*s/2,w*s/2,0], order=1)
PIL.Image.fromarray(npy.uint8(cropped_and_resized_image)).save("output_image_at.jpg")
提前感谢您的反馈
这是OpenCV的实现
# OpenCV implementation of crop/resize using affine transform
import numpy as np
from matplotlib import pyplot as plt
%matplotlib inline
import cv2
src_rgb = cv2.imread('test_img.jpg')
# Source width and height in pixels
src_w_px = 640
src_h_px = 480
# Target width and height in pixels
res_w_px = 640
res_h_px = 480
# Scaling parameter
s = 2.0
Affine_Mat_w = [s, 0, res_w_px/2.0 - s*src_w_px/2.0]
Affine_Mat_h = [0, s, res_h_px/2.0 - s*src_h_px/2.0]
M = np.c_[ Affine_Mat_w, Affine_Mat_h].T
res = cv2.warpAffine(src_rgb, M, (res_w_px, res_h_px))
# Showing the result
plt.figure(figsize=(15,6))
plt.subplot(121); plt.imshow(src_rgb); plt.title('Original image');
plt.subplot(122); plt.imshow(res); plt.title('Image warped Affine transform');
OpenCV实现裁剪图像&&使用仿射变换将大小调整为(des_width, des_height)
import numpy as np
import cv2
def crop_resized_with_affine_transform(img_path, roi_xyxy, des_width, des_height):
src_rgb = cv2.imread(img_path)
'''
image roi
(x0,y0)------------(x1,y1)
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(-,-)------------(x2, y2)
'''
src_points = [[roi_xyxy[0], roi_xyxy[1]], [roi_xyxy[2], roi_xyxy[1]], [roi_xyxy[2], roi_xyxy[3]]]
src_points = np.array(src_points, dtype=np.float32)
des_points = [[0, 0], [des_width, 0], [des_width, des_height]]
des_points = np.array(des_points, dtype=np.float32)
M = cv2.getAffineTransform(src_points, des_points)
crop_and_resized_with_affine_transform = cv2.warpAffine(src_rgb, M, (des_width, des_height))
return crop_and_resized_with_affine_transform
def crop_resized(img_path, roi_xyxy, des_width, des_height):
src_rgb = cv2.imread(img_path)
roi_img = src_rgb[roi_xyxy[1]:roi_xyxy[3], roi_xyxy[0]:roi_xyxy[2]]
resized_roi_img = cv2.resize(roi_img, (des_width, des_height))
return resized_roi_img
if __name__ == "__main__":
'''
Source image from
https://www.whitehouse.gov/wp-content/uploads/2021/04/P20210303AS-1901.jpg
or
https://en.wikipedia.org/wiki/Joe_Biden#/media/File:Joe_Biden_presidential_portrait.jpg
'''
img_path = "Joe_Biden_presidential_portrait.jpg"
# xmin ymin xmax ymax
roi_xyxy = [745, 265, 1675, 1520]
des_width = 480
des_height = 720
crop_and_resized_with_affine_transform = crop_resized_with_affine_transform(img_path, roi_xyxy , des_width, des_height)
resized_roi_img = crop_resized(img_path, roi_xyxy, des_width, des_height)
cv2.imshow("crop_and_resized_with_affine_transform", crop_and_resized_with_affine_transform)
cv2.imwrite("crop_and_resized_with_affine_transform.jpg", crop_and_resized_with_affine_transform)
cv2.imshow("resized_roi_img", resized_roi_img)
cv2.imwrite("resized_roi_img.jpg", resized_roi_img)
cv2.waitKey(0)