amenabe22

import os
from telegram import Update
from langchain_community.llms import LlamaCpp
from langchain.callbacks.manager import CallbackManager
from langchain.chains import LLMChain
from langchain.llms.openai import OpenAI
from langchain.prompts import PromptTemplate
from langchain import OpenAI, LLMChain, PromptTemplate
from langchain.callbacks.streaming_stdout import StreamingStdOutCallbackHandler
from langchain.memory import ConversationBufferWindowMemory, ConversationBufferMemory, ChatMessageHistory

amenabe22

absl-py==2.0.0
astunparse==1.6.3
boto3==1.28.67
botocore==1.31.67
brisque==0.0.15
cachetools==5.3.1
certifi==2022.12.7
chardet==4.0.0
charset-normalizer==3.3.0
click==8.1.7

amenabe22

import os
import numpy as np
from PIL import Image
from skimage import io
from brisque import BRISQUE
from skimage.transform import resize
from skimage.metrics import structural_similarity as ssim


def load_images(image_folder, target_size=(256, 256)):

amenabe22

absl-py==2.0.0
boto3==1.28.67
botocore==1.31.67
cachetools==5.3.1
certifi==2022.12.7
chardet==4.0.0
charset-normalizer==3.3.0
click==8.1.7
contourpy==1.1.1
cycler==0.10.0

amenabe22

import os
import numpy as np
from PIL import Image
from skimage import io
from brisque import BRISQUE
from skimage.transform import resize
from skimage.metrics import structural_similarity as ssim
from deepface_helper import *

amenabe22

import os
import torch
import numpy as np
from PIL import Image
from skimage.metrics import structural_similarity as ssim

# Load the YOLOv5 model
model = torch.hub.load('ultralytics/yolov5:master', 'yolov5s') 

# Load your three images

amenabe22

import json
import csv
from pprint import pprint
from slugify import slugify

def json_to_csv(json_data, csv_file):
    # now we will open a file for writing
    data_file = open(csv_file, 'w')
    
    # create the csv writer object