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Running
on
Zero
File size: 3,604 Bytes
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from PIL import Image
import PIL
import cv2, math,os
import numpy as np
# 最短边为1024，并进行中心裁剪
def resize_image_pil(input_image, min_side=1024):
# 获取图像的宽度和高度
width, height = input_image.size
# 计算缩放比例
scale = min_side / min(height, width)
# 计算新的尺寸
new_width = int(width * scale)
new_height = int(height * scale)
# 调整图像大小
resized_image = input_image.resize((new_width, new_height), Image.ANTIALIAS)
# 计算中心裁剪的位置
crop_top = (new_height - min_side) // 2
crop_left = (new_width - min_side) // 2
# 进行中心裁剪
cropped_image = resized_image.crop((crop_left, crop_top, crop_left + min_side, crop_top + min_side))
return cropped_image
def resize_image_cv2(input_image, min_side=1024, ):
# cv2读取的image
(height, width, _ )= input_image.shape
# print(height, width)
scale = min_side / min(height, width)
# 计算新的尺寸
new_width = int(width * scale)
new_height = int(height * scale)
input_image =cv2.resize(input_image, (new_width, new_height))
# 计算中心裁剪的位置
crop_top = (new_height - min_side) // 2
crop_left = (new_width - min_side) // 2
# 进行中心裁剪
image = input_image[crop_top:crop_top + min_side, crop_left:crop_left + min_side]
return image
def resize_img0(input_image, max_side=1280, min_side=1024,
mode=Image.BILINEAR, base_pixel_number=64):
w, h = input_image.size
ratio = min_side / min(h, w)
w, h = round(ratio*w), round(ratio*h)
ratio = max_side / max(h, w)
input_image = input_image.resize([round(ratio*w), round(ratio*h)], mode)
w_resize_new = (round(ratio * w) // base_pixel_number) * base_pixel_number
h_resize_new = (round(ratio * h) // base_pixel_number) * base_pixel_number
input_image = input_image.resize([w_resize_new, h_resize_new], mode)
return input_image
def resize_img1(input_image, max_side=1280, min_side=1024,
mode=Image.BILINEAR, base_pixel_number=64):
w, h = input_image.size
ratio = min_side / w
w, h = round(ratio*w), round(ratio*h)
input_image = input_image.resize([w, h], mode)
w_resize_new = (w // base_pixel_number) * base_pixel_number
h_resize_new = (h // base_pixel_number) * base_pixel_number
input_image = input_image.resize([w_resize_new, h_resize_new], mode)
return input_image
def resize_img(input_image, max_side=1024, min_side=1024, size=None,
pad_to_max_side=False, mode=Image.BILINEAR, base_pixel_number=64):
w, h = input_image.size
if size is not None:
w_resize_new, h_resize_new = size
else:
ratio = min_side / min(h, w)
w, h = round(ratio * w), round(ratio * h)
ratio = max_side / max(h, w)
input_image = input_image.resize([round(ratio * w), round(ratio * h)], mode)
w_resize_new = (round(ratio * w) // base_pixel_number) * base_pixel_number
h_resize_new = (round(ratio * h) // base_pixel_number) * base_pixel_number
input_image = input_image.resize([w_resize_new, h_resize_new], mode)
if pad_to_max_side:
res = np.ones([max_side, max_side, 3], dtype=np.uint8) * 255
offset_x = (max_side - w_resize_new) // 2
offset_y = (max_side - h_resize_new) // 2
res[offset_y:offset_y + h_resize_new, offset_x:offset_x + w_resize_new] = np.array(input_image)[:, :, :3]
input_image = Image.fromarray(res)
return input_image |