app.py

# from flask import Flask, request, jsonify
from handler import EndpointHandler

# app = Flask(__name__)
# handler = EndpointHandler()

# @app.route('/process_image', methods=['POST'])
# def process_image():
#     data = request.json
#     if data is None:
#         return jsonify({'error': 'No JSON data received'}), 400
    
#     try:
#         result_image = handler(data)
#     except Exception as e:
#         return jsonify({'error': str(e)}), 500
    
#     # Convert PIL image to base64 string
#     buffered = BytesIO()
#     result_image.save(buffered, format="JPEG")
#     result_image_str = base64.b64encode(buffered.getvalue()).decode()

#     return jsonify({'result_image': result_image_str})

# if __name__ == '__main__':
#     app.run(debug=False,port=8001)

import easyocr as ocr  #OCR
import torch
import streamlit as st  #Web App
from PIL import Image #Image Processing
import numpy as np #Image Processing 
from diffusers import StableDiffusionInstructPix2PixPipeline, EulerAncestralDiscreteScheduler


#title
st.title("Make Your Videos More Beautiful with Devticks services")

prompt = st.text_input("Enter your prompt here")
#image uploader
image = st.file_uploader(label = "Upload your image here",type=['png','jpg','jpeg'])


@st.cache
def load_model(): 
    reader = ocr.Reader(['en'],model_storage_directory='.')
    return reader 

reader = load_model() #load model

if image is not None:

    input_image = Image.open(image) #read image
    st.image(input_image) #display image

    with st.spinner("🤖 AI is at Work! "):
        
        model_id = "timbrooks/instruct-pix2pix"
        pipe = StableDiffusionInstructPix2PixPipeline.from_pretrained(model_id, torch_dtype=torch.float16, safety_checker=None)
        pipe.to("cuda")
        pipe.scheduler = EulerAncestralDiscreteScheduler.from_config(pipe.scheduler.config)
        images = pipe(prompt, image=image, num_inference_steps=10, image_guidance_scale=1).images

        images[0].show()
        

        # result_text = [] #empty list for results


        # for text in result:
        #     result_text.append(text[1])

        # st.write(result_text)
    #st.success("Here you go!")
    st.balloons()
else:
    st.write("Upload an Image")

st.caption("🤗")