import matplotlib.pypplot as plt from PIL import Image from IPython.display import display, HTML # Get matplotlib figure as a base64 string fig = plt.gcf() fig.canvas.draw() pil_img = Image.frombytes('RGB', fig.canvas.get_width_height(), fig.canvas.tostring_rgb()) data_url = "data...
from pathlib import Path from unittest.mock import mock_open, patch @@ -32,6 +33,7 @@ make_snowman_image, ) from genai_perf.tokenizer import Tokenizer from PIL import Image mocked_openorca_data = { "features": [ @@ -555,14 +557,12 @@ def test_llm_inputs_with_defaults(self, de...
from PIL import ImageGrabimport ioimport codecs# Pull image from clibpoardimg = ImageGrab.grabclipboard()# Get raw bytesimg_bytes = io.BytesIO()img.save(img_bytes, format='PNG')# Convert bytes to base64base64_data = codecs.encode(img_bytes.getvalue(), 'base64')# Convert base64 data...
# 需要导入模块: from PySide.QtGui import QPixmap [as 别名]# 或者: from PySide.QtGui.QPixmap importfromImage[as 别名]defconvert_bitmap(image, width=None, height=None):pix =Noneifisinstance(image, ImageResource): pix = traitsui_convert_bitmap(image)elifisinstance(image, Image):# image =...
模块: from scss.types import List [as 别名]# 或者: from scss.types.List importfrom_maybe[as 别名]defbackground_noise(density=None, opacity=None, size=None, monochrome=False, intensity=(), color=None, background=None, inline=False):ifnotImage:raiseException("Images manipulation require PIL"...
import torch import numpy as np from PIL import Image from .briarmbg import BriaRMBG @torch.inference_mode() @@ -22,16 +23,20 @@ def pytorch2numpy(imgs, quant=True): @torch.inference_mode() def numpy2pytorch(imgs): """Note: A1111's VAE accepts -1 ~ 1 tensors.""" h = (...
from PIL import Image import numpy as np import cv2 def restore_detail( ic_light_image: np.array, original_image: np.array, blur_radius: int = 5, ) -> Image: h, w, c = ic_light_image.shape original_image = cv2.resize(original_image, (w, h)) if len(ic_light_image.shape) =...
# 需要导入模块: from PIL import Image [as 别名]# 或者: from PIL.Image importfrombytes[as 别名]defgetDecodedColorImage(self):#Get the width and height infowidth, height = tuple(self.size.split(",")) width = int(width) height = int(height)#Decode the concatinated base64 channelsdecoded...
import io, os, math, base64 from datetime import date, time, datetime from PIL import Image from deta import Deta @@ -34,7 +34,6 @@ #* Unique key generator *# #*---*# key = str(math.ceil(datetime.now().timestamp())) # st.write(key) #!---set title and subtitle st....
import time import re import base64 import hmac import hashlib import json import matplotlib.pyplot as plt from http import cookiejar from PIL import Image HEADERS = { 'Connection': 'keep-alive', 'Host': 'www.zhihu.com', 'Referer': 'https://www.zhihu.com/', 'User-Agent': 'Mozilla/...