app.py

import streamlit as st
from PIL import Image
import io
import base64
import google.generativeai as genai
import os
import requests
import random
import numpy as np
import cv2
from rembg import remove
import textwrap
import easyocr
import pytesseract
from fontTools.ttLib import TTFont
from langchain_groq import ChatGroq
import logging

# Load environment variables
from dotenv import load_dotenv
load_dotenv()

# Configure the generative AI model
genai.configure(api_key=os.getenv("GOOGLE_API_KEY"))

generation_config = {
    "temperature": 0,
    "top_p": 1,
    "top_k": 1,
    "max_output_tokens": 2048,
}

model = genai.GenerativeModel(
    model_name="gemini-1.5-pro",
    generation_config=generation_config,
)

API_URL = "https://api-inference.huggingface.co/models/black-forest-labs/FLUX.1-dev"
headers = {"Authorization": f"Bearer {os.getenv('HF_TOKEN')}"}

# Set up Tesseract path
pytesseract.pytesseract.tesseract_cmd = r'C:\Program Files\Tesseract-OCR\tesseract.exe'  # Adjust this path as needed

# Set up Groq LLM
llm = ChatGroq(
    temperature=0.7,
    groq_api_key=os.getenv('GROQ_API_KEY'),
    model_name="llama-3.1-70b-versatile"
)

# Content from agent.py
def generate_advertisement_prompt(description):
    prompt = f"""
    Based on the following detailed description for an advertisement post, image prompt:

    Description: "{description}"

    Generate a detailed image prompt for an AI image generation model, incorporating these elements:

    1. Subject: Describe the main subject or product in the advertisement, including its key features and visual characteristics.

    2. Composition: Explain how the subject should be positioned within the frame, any specific angles or perspectives to highlight its best features.

    3. Background: Detail the setting or environment that complements the subject and reinforces the advertisement's message.

    4. Text Elements: text elemeny should be adverticement purpose like based on the description generate adverticement text.

    5. Style: Describe the overall visual style, color scheme, and mood that best represents the brand and appeals to the target audience.

    6. Additional Elements: List any supporting visual elements, such as logos, icons, or graphics that should be included to enhance the advertisement's impact.

    7. Target Audience: Briefly mention the intended audience to ensure the image resonates with them.

    8. Think in the basis of adverticment designer and combined all 7 points and make a final prompt.

    Please provide a cohesive image prompt that incorporates all these elements into a striking, attention-grabbing advertisement poster, based on the given description. The prompt should be detailed enough to generate a compelling and effective advertisement image.
    """

    response = llm.invoke(prompt)
    return response.content

def advertisement_generator():
    st.title("Advertisement Post Generator")

    post_description = st.text_input("Enter a brief description for your advertisement post:")

    if st.button("Generate Advertisement Elements"):
        if post_description:
            with st.spinner("Generating advertisement elements..."):
                final_prompt = generate_advertisement_prompt(post_description)
                st.subheader("Generated Advertisement Prompt:")
                
                st.text_area(label="Final Prompt", value=final_prompt.strip(), height=200)
        else:
            st.warning("Please enter a description for your advertisement post.")

# Content from image_generation.py
logging.basicConfig(level=logging.DEBUG)
logger = logging.getLogger(__name__)

def query(payload):
    try:
        response = requests.post(API_URL, headers=headers, json=payload)
        response.raise_for_status()
        
        logger.debug(f"API response status code: {response.status_code}")
        logger.debug(f"API response headers: {response.headers}")
        
        return response.content
    except requests.exceptions.RequestException as e:
        logger.error(f"Request failed: {str(e)}")
        st.error(f"Request failed: {str(e)}")
        return None

def increase_image_quality(image, scale_factor):
    width, height = image.size
    new_size = (width * scale_factor, height * scale_factor)
    return image.resize(new_size, Image.LANCZOS)

def generate_poster():
    st.header("Generate Social Media Post")
    post_type = st.selectbox("Select Post Type", ["Instagram advertisement post", "Facebook advertisement post", "Twitter advertisement post", "Other"])
    aspect_ratio = st.selectbox("Select Image Aspect Ratio", ["1:1", "16:9", "4:5", "9:16"])
    
    # Add dimension selection based on aspect ratio
    if aspect_ratio == "1:1":
        dimensions = st.selectbox("Select Image Dimensions", ["1080x1080", "1200x1200", "1500x1500"])
    elif aspect_ratio == "16:9":
        dimensions = st.selectbox("Select Image Dimensions", ["1920x1080", "1280x720", "2560x1440"])
    elif aspect_ratio == "4:5":
        dimensions = st.selectbox("Select Image Dimensions", ["1080x1350", "1200x1500", "1600x2000"])
    elif aspect_ratio == "9:16":
        dimensions = st.selectbox("Select Image Dimensions", ["1080x1920", "1350x2400", "1600x2844"])
    
    # Extract width and height from the selected dimensions
    width, height = map(int, dimensions.split('x'))
    
    design_style = st.selectbox("Select Design Style", [
        "Minimalistic", "Bold/Graphic", "Elegant", "Playful/Fun",
        "Corporate/Professional", "Retro/Vintage", "Modern/Contemporary", "Illustrative/Artistic"
    ])
    
    header = st.text_input("Enter Header for Advertisement:")
    placeholder_text = st.text_input("Enter placeholder text:")
    description = st.text_area("Enter Description for Advertisement:")
    logo = st.file_uploader("Upload Logo (optional)", type=['png', 'jpg', 'jpeg'])
    
    # Add logo position selection
    logo_position = st.selectbox("Select Logo Position", [
        "Top Left", "Top Middle", "Top Right",
        "Left Middle", "Right Middle",
        "Bottom Left", "Bottom Middle", "Bottom Right"
    ])
    
    # Add padding slider
    padding_percent = st.slider("Logo Padding (%)", 1, 10, 2)
    
    num_images = st.number_input("Number of Images", min_value=4, max_value=8, value=4)
    quality_factor = st.number_input("Quality Factor", min_value=1, max_value=4, value=1)

    if st.button("Generate Images"):
        if post_type == "Other":
            full_prompt = f"{header}. A {design_style.lower()} style post with the following elements: {description}, aspect ratio: {aspect_ratio}, dimensions: {width}x{height}, 4k high resolution. Placeholder: {placeholder_text}"
        else:
            full_prompt = f"{header}. A {design_style.lower()} style {post_type.lower()} with the following elements: {description}, aspect ratio: {aspect_ratio}, dimensions: {width}x{height}, 4k high resolution. Placeholder: {placeholder_text}"

        generated_images = []
        for i in range(num_images):
            with st.spinner(f"Generating image {i+1}..."):
                logger.info(f"Generating image {i+1} with prompt: {full_prompt}")
                # Add a random seed to ensure different images
                seed = random.randint(1, 1000000)
                image_bytes = query({"inputs": full_prompt, "parameters": {"seed": seed, "width": width, "height": height}})
                
                if image_bytes:
                    image = Image.open(io.BytesIO(image_bytes))
                    if quality_factor > 1:
                        image = increase_image_quality(image, quality_factor)
                    
                    # Add logo to the selected position if provided
                    if logo:
                        logo_image = Image.open(logo)
                        logo_width = int(image.width * 0.15)  # 15% of the image width
                        logo_height = int(logo_image.height * (logo_width / logo_image.width))
                        logo_image = logo_image.resize((logo_width, logo_height), Image.LANCZOS)
                        
                        padding = int(image.width * (padding_percent / 100))  # Convert percentage to pixels
                        
                        # Calculate logo position based on user selection
                        if logo_position == "Top Left":
                            position = (padding, padding)
                        elif logo_position == "Top Middle":
                            position = ((image.width - logo_width) // 2, padding)
                        elif logo_position == "Top Right":
                            position = (image.width - logo_width - padding, padding)
                        elif logo_position == "Left Middle":
                            position = (padding, (image.height - logo_height) // 2)
                        elif logo_position == "Right Middle":
                            position = (image.width - logo_width - padding, (image.height - logo_height) // 2)
                        elif logo_position == "Bottom Left":
                            position = (padding, image.height - logo_height - padding)
                        elif logo_position == "Bottom Middle":
                            position = ((image.width - logo_width) // 2, image.height - logo_height - padding)
                        else:  # Bottom Right
                            position = (image.width - logo_width - padding, image.height - logo_height - padding)
                        
                        # Create a new image with an alpha channel
                        combined_image = Image.new('RGBA', image.size, (0, 0, 0, 0))
                        combined_image.paste(image, (0, 0))
                        
                        # Convert logo to RGBA if it's not already
                        if logo_image.mode != 'RGBA':
                            logo_image = logo_image.convert('RGBA')
                        
                        combined_image.paste(logo_image, position, logo_image)
                        
                        # Convert back to RGB for compatibility
                        image = combined_image.convert('RGB')
                    
                    generated_images.append(image)
                else:
                    st.error("Failed to generate image")

        # Display generated images
        for i, img in enumerate(generated_images):
            st.image(img, caption=f"Generated Poster {i+1}", use_column_width=True)
            
            # Provide download option for the generated image
            buf = io.BytesIO()
            img.save(buf, format="PNG")
            byte_im = buf.getvalue()
            st.download_button(
                label=f"Download generated poster {i+1}",
                data=byte_im,
                file_name=f"generated_poster_{i+1}.png",
                mime="image/png"
            )

# Content from image_to_image.py
def encode_image(image):
    buffered = io.BytesIO()
    image.save(buffered, format="PNG")
    return base64.b64encode(buffered.getvalue()).decode('utf-8')

def generate_image_prompt(image):
    encoded_image = encode_image(image)
    
    prompt_parts = [
        {"mime_type": "image/png", "data": base64.b64decode(encoded_image)},
        "Analyze this image and generate a detailed prompt that could be used to recreate this image using an AI image generation model. Include key visual elements, style, composition, and any other relevant details but do not include any kind of text elements."
    ]

    response = model.generate_content(prompt_parts)
    return response.text

def generate_new_image(prompt):
    # Add a random seed to ensure different images
    seed = random.randint(1, 1000000)
    payload = {
        "inputs": prompt,
        "parameters": {"seed": seed}
    }
    response = requests.post(API_URL, headers=headers, json=payload)
    return Image.open(io.BytesIO(response.content))

# Part 2: Image Editing

# Content from image_assembled.py
def load_image(image_file):
    img = Image.open(image_file)
    return img

def crop_image(img, left, top, right, bottom):
    return img.crop((left, top, right, bottom))

def resize_image(img, max_size):
    width, height = img.size
    if width > height:
        if width > max_size:
            ratio = max_size / width
            new_size = (max_size, int(height * ratio))
    else:
        if height > max_size:
            ratio = max_size / height
            new_size = (int(width * ratio), max_size)
    return img.resize(new_size, Image.LANCZOS)

def assemble_images(background, images, positions, sizes):
    canvas = background.copy()
    for img, pos, size in zip(images, positions, sizes):
        resized_img = img.resize(size, Image.LANCZOS)
        canvas.paste(resized_img, pos, resized_img if resized_img.mode == 'RGBA' else None)
    return canvas

def drag_and_resize_images(background, images, positions, sizes):
    def on_mouse(event, x, y, flags, param):
        nonlocal dragging, resizing, active_image, offset_x, offset_y, start_size, resize_corner

        if event == cv2.EVENT_LBUTTONDOWN:
            for i, (image, pos, size) in enumerate(zip(images, positions, sizes)):
                ix, iy = pos
                if ix <= x <= ix + size[0] and iy <= y <= iy + size[1]:
                    active_image = i
                    offset_x = x - ix
                    offset_y = y - iy
                    start_size = size
                    
                    # Check if click is near a corner (within 10 pixels)
                    corner_size = 10
                    if (x - ix < corner_size and y - iy < corner_size) or \
                       (ix + size[0] - x < corner_size and y - iy < corner_size) or \
                       (x - ix < corner_size and iy + size[1] - y < corner_size) or \
                       (ix + size[0] - x < corner_size and iy + size[1] - y < corner_size):
                        resizing = True
                        resize_corner = (x - ix, y - iy)
                    else:
                        dragging = True
                    break

        elif event == cv2.EVENT_MOUSEMOVE:
            if dragging:
                positions[active_image] = (x - offset_x, y - offset_y)
            elif resizing:
                dx = x - (positions[active_image][0] + resize_corner[0])
                dy = y - (positions[active_image][1] + resize_corner[1])
                
                if resize_corner[0] < start_size[0] / 2:
                    dx = -dx
                if resize_corner[1] < start_size[1] / 2:
                    dy = -dy
                
                new_width = max(10, start_size[0] + dx)
                new_height = max(10, start_size[1] + dy)
                sizes[active_image] = (int(new_width), int(new_height))

        elif event == cv2.EVENT_LBUTTONUP:
            dragging = False
            resizing = False

    dragging = False
    resizing = False
    active_image = -1
    offset_x, offset_y = 0, 0
    start_size = (0, 0)
    resize_corner = (0, 0)

    window_name = "Drag and Resize Images"
    cv2.namedWindow(window_name)
    cv2.setMouseCallback(window_name, on_mouse)

    while True:
        img_copy = assemble_images(background, images, positions, sizes)
        cv2.imshow(window_name, cv2.cvtColor(np.array(img_copy), cv2.COLOR_RGB2BGR))
        key = cv2.waitKey(1) & 0xFF
        if key == 27:  # ESC key
            break

    cv2.destroyAllWindows()
    return positions, sizes, img_copy

# Content from text_replacer.py
def detect_text(image):
    reader = easyocr.Reader(['en'])
    img_array = np.array(image)
    results = reader.readtext(img_array)
    return [(text, box) for (box, text, _) in results]

def get_text_color(image, box):
    x, y = int(box[0][0]), int(box[0][1])
    rgb_image = image.convert('RGB')
    color = rgb_image.getpixel((x, y))
    return color

def detect_font(image, box):
    x, y, w, h = int(box[0][0]), int(box[0][1]), int(box[2][0] - box[0][0]), int(box[2][1] - box[0][1])
    cropped = image.crop((x, y, x+w, y+h))
    
    # Use Tesseract to detect font
    custom_config = r'--oem 3 --psm 6 -c tessedit_char_whitelist=ABCDEFGHIJKLMNOPQRSTUVWXYZabcdefghijklmnopqrstuvwxyz0123456789'
    font_info = pytesseract.image_to_data(cropped, config=custom_config, output_type=pytesseract.Output.DICT)
    
    # Check if 'font' key exists in font_info
    if 'font' in font_info:
        # Get the most common font
        fonts = [f for f in font_info['font'] if f != '']
        if fonts:
            most_common_font = max(set(fonts), key=fonts.count)
            return most_common_font
    
    return "arialbd"  # Default to Bold Arial if no font detected or 'font' key not present

def replace_text_in_image(image, text_to_replace, new_text, new_color):
    img_array = np.array(image)
    for (text, box) in detect_text(image):
        if text == text_to_replace:
            x, y, w, h = int(box[0][0]), int(box[0][1]), int(box[2][0] - box[0][0]), int(box[2][1] - box[0][1])
            
            # Detect the font of the original text
            detected_font = detect_font(image, box)
            
            # Create a mask for the text area
            mask = np.zeros(img_array.shape[:2], dtype=np.uint8)
            cv2.rectangle(mask, (x, y), (x+w, y+h), 255, -1)

            # Inpaint the text area
            img_array = cv2.inpaint(img_array, mask, 3, cv2.INPAINT_TELEA)

            image = Image.fromarray(img_array)
            draw = ImageDraw.Draw(image)
            font_size = int(h * 0.8) 
            
            supported_extensions = ['.ttf', '.otf', '.woff', '.woff2']
            font_path = None
            for ext in supported_extensions:
                if os.path.exists(f"{detected_font}{ext}"):
                    font_path = f"{detected_font}{ext}"
                    break
            if not font_path:
                font_path = "arialbd.ttf"  # Default to Bold Arial if no supported font found
            
            font = ImageFont.truetype(font_path, font_size)
            
            draw.text((x, y), new_text, font=font, fill=new_color)
            return image

    return Image.fromarray(img_array)

# Content from text.py
def put_text(img, text, x_value, y_value, color):
    if img is None:
        raise ValueError("Image not found or could not be loaded.")
    
    font = cv2.FONT_HERSHEY_DUPLEX
    wrapped_text = textwrap.wrap(text, width=30)
    font_size = 1
    font_thickness = 2

    for i, line in enumerate(wrapped_text):
        textsize = cv2.getTextSize(line, font, font_size, font_thickness)[0]

        gap = textsize[1] + 10
        y = y_value + i * gap
        x = x_value
        cv2.putText(img, line, (x, y), font,
                    font_size,
                    color,
                    font_thickness,
                    lineType = cv2.LINE_AA)

def drag_text(img, texts):
    def on_mouse(event, x, y, flags, param):
        nonlocal dragging, active_text, offset_x, offset_y

        if event == cv2.EVENT_LBUTTONDOWN:
            for i, (text, pos, color) in enumerate(texts):
                tx, ty = pos
                wrapped_text = textwrap.wrap(text, width=30)
                text_height = len(wrapped_text) * 30  # Approximate text height
                text_width = max(cv2.getTextSize(line, cv2.FONT_HERSHEY_DUPLEX, 1, 2)[0][0] for line in wrapped_text)
                if tx <= x <= tx + text_width and ty - 30 <= y <= ty + text_height:  # Expanded clickable area
                    dragging = True
                    active_text = i
                    offset_x = x - tx
                    offset_y = y - ty
                    break

        elif event == cv2.EVENT_MOUSEMOVE:
            if dragging:
                texts[active_text] = (texts[active_text][0], (x - offset_x, y - offset_y), texts[active_text][2])

        elif event == cv2.EVENT_LBUTTONUP:
            dragging = False

    dragging = False
    active_text = -1
    offset_x, offset_y = 0, 0

    window_name = "Drag Text"
    cv2.namedWindow(window_name)
    cv2.setMouseCallback(window_name, on_mouse)

    while True:
        img_copy = img.copy()
        for text, (x, y), color in texts:
            put_text(img_copy, text, x, y, color)

        cv2.imshow(window_name, img_copy)
        key = cv2.waitKey(1) & 0xFF
        if key == 27:  # ESC key
            break

    cv2.destroyAllWindows()
    return texts, img_copy

# Content from background_remove.py
def remove_background(image):
    # Convert PIL Image to numpy array
    img_array = np.array(image)
    
    # Remove background
    result = remove(img_array)
    
    # Convert back to PIL Image
    return Image.fromarray(result)

# Main Streamlit App
def main():
    st.title("Image Generation and Editing App")

    # Sidebar for navigation
    page = st.sidebar.selectbox("Choose a function", ["Text to Image Generation", "Image Editing", "Poster Generation", "Advertisement Generator"])

    if page == "Text to Image Generation":
        text_to_image_generation()
    elif page == "Image Editing":
        image_editing()
    elif page == "Poster Generation":
        generate_poster()
    elif page == "Advertisement Generator":
        advertisement_generator()

def text_to_image_generation():
    st.header("Text to Image Generation")

    # Image to Image Generation
    st.subheader("Image to Image Generation")
    uploaded_file = st.file_uploader("Choose an image:", type=["png", "jpg", "jpeg"])
    if uploaded_file is not None:
        image = Image.open(uploaded_file)
        st.image(image, caption="Uploaded Image", use_column_width=True)

        if st.button("Generate Image Prompt"):
            with st.spinner("Analyzing image and generating prompt..."):
                generated_prompt = generate_image_prompt(image)
                st.subheader("Generated Image Prompt:")
                st.text_area(label="", value=generated_prompt.strip(), height=200, key="generated_prompt", disabled=True)
                st.session_state['saved_prompt'] = generated_prompt.strip()

        # Add multiple text elements
        st.subheader("Add Text Elements")
        num_text_elements = st.number_input("Number of text elements to add:", min_value=1, max_value=5, value=1)
        text_elements = []
        for i in range(num_text_elements):
            text_element = st.text_input(f"Enter text {i+1} to add to the image:")
            if text_element:
                text_elements.append(f'text on image: "{text_element}"')
        text_element_prompt = ", ".join(text_elements)

        # User input prompt
        st.subheader("Additional Prompt")
        user_prompt = st.text_input("Enter additional prompt details:")

        # Combine prompts
        saved_prompt = st.session_state.get('saved_prompt', '')
        final_prompt = f"{saved_prompt}, {text_element_prompt}, {user_prompt}".strip()
        
        st.subheader("Final Prompt")
        final_prompt_area = st.text_area("Final prompt for image generation:", value=final_prompt, height=150, key="final_prompt")

        if st.button("Generate New Images"):
            with st.spinner("Generating new images..."):
                col1, col2 = st.columns(2)
                for i in range(4):
                    new_image = generate_new_image(final_prompt_area)
                    if i % 2 == 0:
                        with col1:
                            st.image(new_image, caption=f"Generated Image {i+1}", use_column_width=True)
                    else:
                        with col2:
                            st.image(new_image, caption=f"Generated Image {i+1}", use_column_width=True)

def image_editing():
    st.header("Image Editing")

    # Background Removal
    st.subheader("Background Removal")
    bg_remove_file = st.file_uploader("Choose an image for background removal", type=["jpg", "jpeg", "png"])
    if bg_remove_file is not None:
        image = Image.open(bg_remove_file)
        st.image(image, caption="Original Image", use_column_width=True)
        if st.button("Remove Background"):
            result = remove_background(image)
            st.image(result, caption="Image with Background Removed", use_column_width=True)
            buf = io.BytesIO()
            result.save(buf, format="PNG")
            byte_im = buf.getvalue()
            st.download_button(label="Download Result", data=byte_im, file_name="result.png", mime="image/png")

    # Image Assembly
    st.subheader("Image Assembly")
    background_file = st.file_uploader("Choose a background image", type=['png', 'jpg', 'jpeg'])
    if background_file:
        background = load_image(background_file)
        background = resize_image(background, 800)
        st.image(background, caption="Background Image", use_column_width=True)

        uploaded_files = st.file_uploader("Choose foreground images", accept_multiple_files=True, type=['png', 'jpg', 'jpeg'])
        if uploaded_files:
            images = [load_image(file) for file in uploaded_files]
            cropped_images = []
            for i, img in enumerate(images):
                st.subheader(f"Image {i+1}")
                st.image(img, use_column_width=True)
                
                st.write(f"Crop image {i+1}")
                col1, col2 = st.columns(2)
                with col1:
                    left = st.slider(f"Left crop for image {i+1}", 0, img.width, 0)
                    right = st.slider(f"Right crop for image {i+1}", 0, img.width, img.width)
                with col2:
                    top = st.slider(f"Top crop for image {i+1}", 0, img.height, 0)
                    bottom = st.slider(f"Bottom crop for image {i+1}", 0, img.height, img.height)
                
                cropped_img = crop_image(img, left, top, right, bottom)
                resized_img = resize_image(cropped_img, 200)
                cropped_images.append(resized_img)
                st.image(resized_img, caption=f"Cropped and Resized Image {i+1}", use_column_width=True)

            if 'positions' not in st.session_state:
                st.session_state.positions = [(0, 0) for _ in cropped_images]
            if 'sizes' not in st.session_state:
                st.session_state.sizes = [img.size for img in cropped_images]

            if st.button("Drag, Resize, and Assemble Images"):
                positions, sizes, assembled_image = drag_and_resize_images(background, cropped_images, st.session_state.positions, st.session_state.sizes)
                st.session_state.positions = positions
                st.session_state.sizes = sizes
                st.image(assembled_image, caption="Assembled Image", use_column_width=True)

            if st.button("Finalize Assembly"):
                assembled_image = assemble_images(background, cropped_images, st.session_state.positions, st.session_state.sizes)
                st.image(assembled_image, caption="Final Assembled Image", use_column_width=True)
                
                buf = io.BytesIO()
                assembled_image.save(buf, format="PNG")
                byte_im = buf.getvalue()
                st.download_button(label="Download Assembled Image", data=byte_im, file_name="assembled_image.png", mime="image/png")

    # Text Overlay
    st.subheader("Text Overlay")
    text_overlay_file = st.file_uploader("Choose an image for text overlay", type=["jpg", "jpeg", "png"])
    if text_overlay_file is not None:
        image = Image.open(text_overlay_file)
        img_array = np.array(image)
        
        st.image(image, caption='Uploaded Image', use_column_width=True)
        
        texts = []
        num_texts = st.number_input("Number of text overlays", min_value=1, value=1)
        
        for i in range(num_texts):
            text = st.text_area(f"Enter text to overlay #{i+1} (multiple lines supported):")
            x_value = st.slider(f"X position for text #{i+1}", 0, img_array.shape[1], 50)
            y_value = st.slider(f"Y position for text #{i+1}", 0, img_array.shape[0], 50 + i*50)
            color = st.color_picker(f"Choose color for text #{i+1}", '#000000')
            color = tuple(int(color.lstrip('#')[i:i+2], 16) for i in (0, 2, 4))
            texts.append((text, (x_value, y_value), color))
        
        if st.button("Add Text and Drag"):
            img_with_text = img_array.copy()
            updated_texts, updated_img = drag_text(img_with_text, texts)
            result_image = Image.fromarray(updated_img)
            st.image(result_image, caption='Image with Dragged Text Overlay', use_column_width=True)
            
            buf = io.BytesIO()
            result_image.save(buf, format="PNG")
            st.download_button(label="Download Updated Image", data=buf.getvalue(), file_name="image_with_dragged_text.png", mime="image/png")

    # Text Replacement
    st.subheader("Text Replacement")
    text_replace_file = st.file_uploader("Choose an image for text replacement", type=["jpg", "jpeg", "png"])
    if text_replace_file is not None:
        image = Image.open(text_replace_file)
        st.image(image, caption='Current Image', use_column_width=True)

        text_results = detect_text(image)
        
        st.subheader("Detected Text:")
        
        for i, (text, box) in enumerate(text_results):
            if text.strip() and text not in st.session_state.get('replaced_texts', []):
                st.text(f"{i+1}. {text}")
                
                new_text = st.text_input(f"Enter new text for '{text}':", value=text, key=f"new_text_{i}")
                new_color = st.color_picker(f"Choose color for new text '{new_text}':", '#000000', key=f"color_{i}")
                
                if st.button(f"Replace '{text}'", key=f"replace_{i}"):
                    st.session_state.edited_image = replace_text_in_image(image, text, new_text, new_color)
                    if 'replaced_texts' not in st.session_state:
                        st.session_state.replaced_texts = []
                    st.session_state.replaced_texts.append(text)
                    st.image(st.session_state.edited_image, caption='Edited Image', use_column_width=True)
                    text_results[i] = (new_text, box)
        
        if hasattr(st.session_state, 'edited_image') and st.session_state.edited_image is not None:
            buf = io.BytesIO()
            st.session_state.edited_image.save(buf, format="PNG")
            byte_im = buf.getvalue()
            st.download_button(label="Download edited image", data=byte_im, file_name="edited_image.png", mime="image/png")

if __name__ == "__main__":
    main()