72 lines
1.8 KiB
Python
72 lines
1.8 KiB
Python
import base64
|
|
import io
|
|
|
|
import numpy as np
|
|
import requests
|
|
import torch
|
|
from PIL import Image
|
|
|
|
|
|
# Tensor to PIL
|
|
def tensor_to_pil(image):
|
|
return Image.fromarray(np.clip(255. * image.cpu().numpy().squeeze(), 0, 255).astype(np.uint8))
|
|
|
|
|
|
# Convert PIL to Tensor
|
|
def pil_to_tensor(image):
|
|
return torch.from_numpy(np.array(image).astype(np.float32) / 255.0).unsqueeze(0)
|
|
|
|
|
|
def base64_to_image(base64_string):
|
|
# 去除前缀
|
|
base64_list = base64_string.split(",", 1)
|
|
if len(base64_list) == 2:
|
|
prefix, base64_data = base64_list
|
|
else:
|
|
base64_data = base64_list[0]
|
|
|
|
# 从base64字符串中解码图像数据
|
|
image_data = base64.b64decode(base64_data)
|
|
|
|
# 创建一个内存流对象
|
|
image_stream = io.BytesIO(image_data)
|
|
|
|
# 使用PIL的Image模块打开图像数据
|
|
image = Image.open(image_stream)
|
|
|
|
return image
|
|
|
|
|
|
def image_to_base64(pli_image, pnginfo=None):
|
|
# 创建一个BytesIO对象，用于临时存储图像数据
|
|
image_data = io.BytesIO()
|
|
|
|
# 将图像保存到BytesIO对象中，格式为PNG
|
|
pli_image.save(image_data, format='PNG', pnginfo=pnginfo)
|
|
|
|
# 将BytesIO对象的内容转换为字节串
|
|
image_data_bytes = image_data.getvalue()
|
|
|
|
# 将图像数据编码为Base64字符串
|
|
encoded_image = "data:image/png;base64," + base64.b64encode(image_data_bytes).decode('utf-8')
|
|
|
|
return encoded_image
|
|
|
|
|
|
def read_image_from_url(image_url):
|
|
s = requests.Session()
|
|
s.keep_alive = False
|
|
response = s.get(image_url, verify=False)
|
|
img = Image.open(io.BytesIO(response.content))
|
|
return img
|
|
|
|
|
|
def hex_to_rgba(hex_color):
|
|
hex_color = hex_color.lstrip('#')
|
|
r, g, b = tuple(int(hex_color[i:i + 2], 16) for i in (0, 2, 4))
|
|
if len(hex_color) == 8:
|
|
a = int(hex_color[6:8], 16)
|
|
else:
|
|
a = 255
|
|
return r, g, b, a
|