import cv2
import numpy as np
from PIL import Image

cap = cv2.VideoCapture(0)

while True:
    ret, frame = cap.read()
    if not ret:
        break

    hsv = cv2.cvtColor(frame, cv2.COLOR_BGR2HSV)

    lower_blue = np.array([100, 150, 50])
    upper_blue = np.array([130, 255, 255])

    lower_green = np.array([40, 70, 70])
    upper_green = np.array([80, 255, 255])

    mask_blue = cv2.inRange(hsv, lower_blue, upper_blue)
    mask_green = cv2.inRange(hsv, lower_green, upper_green)

    kernel = np.ones((5, 5), np.uint8)
    mask_blue = cv2.erode(mask_blue, kernel, iterations=1)
    mask_blue = cv2.dilate(mask_blue, kernel, iterations=2)

    mask_green = cv2.erode(mask_green, kernel, iterations=1)
    mask_green = cv2.dilate(mask_green, kernel, iterations=2)

    bbox_blue = Image.fromarray(mask_blue).getbbox()
    bbox_green = Image.fromarray(mask_green).getbbox()

    # Draw rectangles
    if bbox_blue:
        x1, y1, x2, y2 = bbox_blue
        frame = cv2.rectangle(frame, (x1, y1), (x2, y2), (255, 0, 0), 2)

    if bbox_green:
        x1, y1, x2, y2 = bbox_green
        frame = cv2.rectangle(frame, (x1, y1), (x2, y2), (0, 255, 0), 2)

    cv2.imshow("Color Detection (Blue & Green)", frame)

    if cv2.waitKey(1) & 0xFF == ord('q'):
        break

cap.release()
cv2.destroyAllWindows()

pip install opencv-python

from aiogram import Bot, Dispatcher, types
from aiogram.types import Message
from aiogram.filters import Command
import asyncio
import os

BOT_TOKEN = "bot_token"

dp = Dispatcher()

@dp.message(Command(commands=["start"]))
async def start(message: Message):
    await message.answer("👋 Hello! I am an Echo Bot. Send me any message and I will repeat it!")

@dp.message()
async def echo(message: Message):
    await message.answer(message.text)

async def main():
    try:
        bot = Bot(token=BOT_TOKEN)
        await dp.start_polling(bot)
    finally:
        await bot.session.close()

if __name__ == "__main__":
    asyncio.run(main())

pip install aiogram

import instaloader

def InstagramDownloader(shortcode: str):
    L = instaloader.Instaloader()
    post = instaloader.Post.from_shortcode(L.context, shortcode)
    return {'title': post.title, "caption": post.caption, "rasm": post.url, "video": post.video_url, "turi": post.typename}

# https://www.instagram.com/reel/DNehZkaR6LI/?utm_source=ig_web_copy_link&igsh=MzRlODBiNWFlZA== # shortcode (id): DNehZkaR6LI
print(InstagramDownloader("DNehZkaR6LI")) 

pip install instaloader

from langchain_huggingface import HuggingFaceEmbeddings
from langchain.vectorstores import FAISS
from langchain.document_loaders import PyPDFLoader
from langchain.text_splitter import RecursiveCharacterTextSplitter
from langchain.chains.conversational_retrieval.base import ConversationalRetrievalChain
from langchain.memory import ConversationBufferMemory
from langchain_google_genai import ChatGoogleGenerativeAI
import os

os.environ["HUGGINGFACEHUB_API_TOKEN"] = "HUGGINGFACE_API_TOKEN"
os.environ["GOOGLE_API_KEY"] = "GOOGLE_API_KEY"

loader = PyPDFLoader("fayl.pdf")
documents = loader.load()

splitter = RecursiveCharacterTextSplitter(chunk_size=1000, chunk_overlap=200)
docs = splitter.split_documents(documents)

embeddings = HuggingFaceEmbeddings(model_name="sentence-transformers/all-MiniLM-L6-v2")

vectorstore = FAISS.from_documents(docs, embeddings)

llm = ChatGoogleGenerativeAI(model="gemini-2.5-pro", temperature=0.3)

memory = ConversationBufferMemory(memory_key="chat_history", return_messages=True)

qa = ConversationalRetrievalChain.from_llm(
    llm=llm,
    retriever=vectorstore.as_retriever(),
    memory=memory
)

print("📚 PDF Chatbot ready! Type 'exit' to quit.\n")
while True:
    query = input("You: ")
    if query.lower() in ["exit", "quit"]:
        break
    result = qa({"question": query})
    print("Bot:", result["answer"])

pip install -r requirements.txt

import streamlit as st

st.write("Hello World")

pip install streamlit

streamlit run [python_faylingizni_nomi].py

pip install telethon

# pip install google-genai

from google import genai

client = genai.Client(api_key="")

javob = client.models.generate_content(
    model="gemini-2.5-flash",
    contents="Salom sen kimsan"
)

print(javob.text)

pip install google-genai

pip install osonbot

from aiogram import Bot, Dispatcher, types
from aiogram.filters import CommandStart
import asyncio

dp = Dispatcher()

@dp.message(CommandStart())
async def start(message: types.Message):
     await message.answer(f"Salom {message.from_user.first_name}")

@dp.message()
async def echo(message: types.Message):
     await message.answer(message.text)

async def main():
     bot = Bot("token")
     await dp.start_polling(bot)

asyncio.run(main())

from telebot import Bot

bot = Bot("token")

@bot.message_handler(commands=['start'])
def start(message):
     bot.send_message(message.chat.id, f"Salom {message.from_user.first_name}")

@bot.message_handler()
def echoo(message):
     bot.send_message(message.chat.id, message.text)

bot.infinity_polling()

from osonbot import Bot

bot = Bot("token")

bot.when("/start", "Salom {first_name}")
bot.when("*", "{message_text}")

bot.run()