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import gradio as gr
import http.client
import json
import requests
import base64
import os
from dotenv import load_dotenv
from openai import OpenAI
# Load environment variables
load_dotenv()
# Function to upload image to imgbb
def upload_image_to_imgbb(image_path):
try:
with open(image_path, "rb") as file:
url = "https://api.imgbb.com/1/upload"
payload = {
"key": os.getenv("IMGBB_API_KEY"),
"image": base64.b64encode(file.read()).decode()
}
res = requests.post(url, data=payload)
res.raise_for_status() # Raises an HTTPError for bad responses
return res.json()['data']['url']
except Exception as e:
return f"Error uploading image: {str(e)}"
# OCR API request
def get_ocr_results(image_url):
try:
conn = http.client.HTTPSConnection("ocr43.p.rapidapi.com")
payload = f"-----011000010111000001101001\r\nContent-Disposition: form-data; name=\"url\"\r\n\r\n{image_url}\r\n-----011000010111000001101001--\r\n\r\n"
headers = {
'x-rapidapi-key': os.getenv("RAPIDAPI_KEY"),
'x-rapidapi-host': "ocr43.p.rapidapi.com",
'Content-Type': "multipart/form-data; boundary=---011000010111000001101001"
}
conn.request("POST", "/v1/results", payload, headers)
res = conn.getresponse()
data = res.read()
return data.decode("utf-8")
except Exception as e:
return f"Error in OCR processing: {str(e)}"
# OpenAI API configuration
openai_client = OpenAI(api_key=os.getenv("OPENAI_API_KEY"))
# Function to process OCR results with OpenAI
def process_ocr_with_gpt(ocr_results):
try:
prompt = f"""
You are an AI assistant tasked with processing OCR results and providing a clean, formatted output.
Here are the OCR results:
{ocr_results}
Please process this information and provide a clean, well-formatted output. If there are any obvious errors in the OCR, please correct them. Format the output in a clear and readable manner.
"""
response = openai_client.chat.completions.create(
model="gpt-3.5-turbo",
messages=[
{"role": "system", "content": "You are a helpful assistant that processes OCR results."},
{"role": "user", "content": prompt}
]
)
return response.choices[0].message.content
except Exception as e:
return f"Error in GPT processing: {str(e)}"
# Gradio interface function
def process_image(image):
try:
# Save the image temporarily and get its path
image_path = "temp_image.png"
image.save(image_path)
# Upload image to imgbb and get URL
image_url = upload_image_to_imgbb(image_path)
if image_url.startswith("Error"):
return image_url, "Failed to process due to image upload error"
# Get OCR results
ocr_results = get_ocr_results(image_url)
if ocr_results.startswith("Error"):
return ocr_results, "Failed to process due to OCR error"
# Process with GPT
processed_results = process_ocr_with_gpt(ocr_results)
# Clean up temporary file
os.remove(image_path)
return ocr_results, processed_results
except Exception as e:
return f"Error in image processing: {str(e)}", "Failed to process due to an error"
# Create Gradio interface
iface = gr.Interface(
fn=process_image,
inputs=gr.Image(type="pil"),
outputs=[
gr.Textbox(label="OCR Results"),
gr.Textbox(label="Processed Results")
],
title="OCR and Text Processing App",
description="Upload an image to extract text and process it."
)
# Launch the app
iface.launch()
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