Python

brew install micromamba

python -m pip install rich

from rich import print

print("Hello, [bold magenta]World[/bold magenta]!", ":vampire:", locals())

import logging

# 配置日志
logging.basicConfig(level=logging.INFO)  # 设置最低日志级别
logging.debug('这是调试信息')    # 不会显示（默认级别为 INFO）
logging.info('这是普通信息')     # INFO 级别
logging.warning('这是警告信息')  # WARNING 级别
logging.error('这是错误信息')    # ERROR 级别
logging.critical('这是严重错误') # CRITICAL 级别

import gizeh

# 创建一个表面
surface = gizeh.Surface(width=200, height=200) 
# 画一个圆
circle = gizeh.circle(r=30, xy=(100,100), fill=(1,0,0))
circle.draw(surface)
# 保存图像
surface.get_npimage()
surface.write_png("circle.png")

python manage.py startapp first

pip install djangorestframework

INSTALLED_APPS = [
    'rest_framework',
]

# 下面的配置根据项目需要进行设置
REST_FRAMEWORK = {
    # 配置默认页面大小
    # 'PAGE_SIZE': 10,
    # 配置默认的分页类
    # 'DEFAULT_PAGINATION_CLASS': '...',
    # 配置异常处理器
    # 'EXCEPTION_HANDLER': '...',
    # 配置默认解析器
    # 'DEFAULT_PARSER_CLASSES': (
    #     'rest_framework.parsers.JSONParser',
    #     'rest_framework.parsers.FormParser',
    #     'rest_framework.parsers.MultiPartParser',
    # ),
    # 配置默认限流类
    # 'DEFAULT_THROTTLE_CLASSES': (
    #     '...'
    # ),
    # 配置默认授权类
    # 'DEFAULT_PERMISSION_CLASSES': (
    #     '...',
    # ),
    # 配置默认认证类
    # 'DEFAULT_AUTHENTICATION_CLASSES': (
    #     '...',
    # ),
}

pip install pyjwt

payload = {
    'exp': datetime.datetime.utcnow() + datetime.timedelta(days=1),
    'userid': 10001
}
token = jwt.encode(payload, settings.SECRET_KEY).decode()

try:
    token = 'eyJ0eXAiOiJKV1QiLCJhbGciOiJIUzI1NiJ9.eyJleHAiOjE1OTQ4NzIzOTEsInVzZXJpZCI6MTAwMDF9.FM-bNxemWLqQQBIsRVvc4gq71y42I9m2zt5nlFxNHUo'
    payload = jwt.decode(token, settings.SECRET_KEY)
except InvalidTokenError:
    raise AuthenticationFailed('无效的令牌或令牌已经过期')

from robyn import Robyn

app = Robyn(__file__)

@app.get("/")
async def h(request):
    return "Hello, world!"

app.start(port=8080)

import falcon

class ThingsResource:
    def on_get(self, req, resp):
        resp.text = "Hello, Falcon!"

app = falcon.App()
app.add_route('/things', ThingsResource())

import flet
from flet import IconButton, Page, Row, TextField, icons

def main(page: Page):
    page.title = "Flet counter example"
    page.vertical_alignment = "center"

    txt_number = TextField(value="0", text_align="right", width=100)

    def minus_click(e):
        txt_number.value = str(int(txt_number.value) - 1)
        page.update()

    def plus_click(e):
        txt_number.value = str(int(txt_number.value) + 1)
        page.update()

    page.add(
        Row(
            [
                IconButton(icons.REMOVE, on_click=minus_click),
                txt_number,
                IconButton(icons.ADD, on_click=plus_click),
            ],
            alignment="center",
        )
    )

flet.app(target=main)

pip install surya-ocr

from textual.app import App, ComposeResult
from textual.widgets import Footer, Header


class StopwatchApp(App):
    """A Textual app to manage stopwatches."""

    BINDINGS = [("d", "toggle_dark", "Toggle dark mode")]

    def compose(self) -> ComposeResult:
        """Create child widgets for the app."""
        yield Header()
        yield Footer()

    def action_toggle_dark(self) -> None:
        """An action to toggle dark mode."""
        self.theme = (
            "textual-dark" if self.theme == "textual-light" else "textual-light"
        )


if __name__ == "__main__":
    app = StopwatchApp()
    app.run()

import dlib
import cv2
import numpy as np
import math
predictor_path='shape_predictor_68_face_landmarks.dat'
 
#使用dlib自带的frontal_face_detector作为我们的特征提取器
detector = dlib.get_frontal_face_detector()
predictor = dlib.shape_predictor(predictor_path)

def landmark_dec_dlib_fun(img_src):
    img_gray = cv2.cvtColor(img_src,cv2.COLOR_BGR2GRAY)
 
    land_marks = []
 
    rects = detector(img_gray,0)
 
    for i in range(len(rects)):
        land_marks_node = np.matrix([[p.x,p.y] for p in predictor(img_gray,rects[i]).parts()])
        # for idx,point in enumerate(land_marks_node):
        #     # 68点坐标
        #     pos = (point[0,0],point[0,1])
        #     print(idx,pos)
        #     # 利用cv2.circle给每个特征点画一个圈，共68个
        #     cv2.circle(img_src, pos, 5, color=(0, 255, 0))
        #     # 利用cv2.putText输出1-68
        #     font = cv2.FONT_HERSHEY_SIMPLEX
        #     cv2.putText(img_src, str(idx + 1), pos, font, 0.8, (0, 0, 255), 1, cv2.LINE_AA)
        land_marks.append(land_marks_node)
 
    return land_marks
'''
方法： Interactive Image Warping 局部平移算法
'''
 
 
def localTranslationWarp(srcImg,startX,startY,endX,endY,radius):
 
    ddradius = float(radius * radius)
    copyImg = np.zeros(srcImg.shape, np.uint8)
    copyImg = srcImg.copy()
 
    # 计算公式中的|m-c|^2
    ddmc = (endX - startX) * (endX - startX) + (endY - startY) * (endY - startY)
    H, W, C = srcImg.shape
    for i in range(W):
        for j in range(H):
            #计算该点是否在形变圆的范围之内
            #优化，第一步，直接判断是会在（startX,startY)的矩阵框中
            if math.fabs(i-startX)>radius and math.fabs(j-startY)>radius:
                continue
 
            distance = ( i - startX ) * ( i - startX) + ( j - startY ) * ( j - startY )
 
            if(distance < ddradius):
                #计算出（i,j）坐标的原坐标
                #计算公式中右边平方号里的部分
                ratio=(  ddradius-distance ) / ( ddradius - distance + ddmc)
                ratio = ratio * ratio
 
                #映射原位置
                UX = i - ratio  * ( endX - startX )
                UY = j - ratio  * ( endY - startY )
 
                #根据双线性插值法得到UX，UY的值
                value = BilinearInsert(srcImg,UX,UY)
                #改变当前 i ，j的值
                copyImg[j,i] =value
 
    return copyImg

#双线性插值法
def BilinearInsert(src,ux,uy):
    w,h,c = src.shape
    if c == 3:
        x1=int(ux)
        x2=x1+1
        y1=int(uy)
        y2=y1+1
 
        part1=src[y1,x1].astype(np.float)*(float(x2)-ux)*(float(y2)-uy)
        part2=src[y1,x2].astype(np.float)*(ux-float(x1))*(float(y2)-uy)
        part3=src[y2,x1].astype(np.float) * (float(x2) - ux)*(uy-float(y1))
        part4 = src[y2,x2].astype(np.float) * (ux-float(x1)) * (uy - float(y1))
 
        insertValue=part1+part2+part3+part4
        return insertValue.astype(np.int8)

def face_thin_auto(src):
 
    landmarks = landmark_dec_dlib_fun(src)
 
    #如果未检测到人脸关键点，就不进行瘦脸
    if len(landmarks) == 0:
        return
 
    for landmarks_node in landmarks:
        left_landmark= landmarks_node[3]
        left_landmark_down=landmarks_node[5]
 
        right_landmark = landmarks_node[13]
        right_landmark_down = landmarks_node[15]
 
        endPt = landmarks_node[30]
 
 
        #计算第4个点到第6个点的距离作为瘦脸距离
        r_left=math.sqrt((left_landmark[0,0]-left_landmark_down[0,0])*(left_landmark[0,0]-left_landmark_down[0,0])+
                         (left_landmark[0,1] - left_landmark_down[0,1]) * (left_landmark[0,1] - left_landmark_down[0, 1]))
 
        # 计算第14个点到第16个点的距离作为瘦脸距离
        r_right=math.sqrt((right_landmark[0,0]-right_landmark_down[0,0])*(right_landmark[0,0]-right_landmark_down[0,0])+
                         (right_landmark[0,1] -right_landmark_down[0,1]) * (right_landmark[0,1] -right_landmark_down[0, 1]))
 
        #瘦左边脸
        thin_image = localTranslationWarp(src,left_landmark[0,0],left_landmark[0,1],endPt[0,0],endPt[0,1],r_left)
        #瘦右边脸
        thin_image = localTranslationWarp(thin_image, right_landmark[0,0], right_landmark[0,1], endPt[0,0],endPt[0,1], r_right)
 
    #显示
    cv2.imshow('thin',thin_image)
    cv2.imwrite('thin.jpg',thin_image)

def main():
    src = cv2.imread('timg4.jpg')
    cv2.imshow('src', src)
    face_thin_auto(src)
    cv2.waitKey(0)
 
if __name__ == '__main__':
    main()