import gradio as gr
import pytesseract
import cv2
import os
import numpy as np
from annif_client import AnnifClient

def get_annif_projects():
    try:
        annif = AnnifClient()
        projects = annif.projects
        if not projects:
            raise ValueError("No projects found from Annif client")
        proj_ids = [project["project_id"] for project in projects]
        proj_names = [project["name"] for project in projects]
        return annif, proj_ids, proj_names
    except Exception as e:
        print(f"Error initializing Annif client: {str(e)}")
        return None, [], []

annif, proj_ids, proj_names = get_annif_projects()

def process(image, project_num: int, lang: str = "eng"):
    try:
        if not proj_ids:
            raise ValueError("No Annif projects available")

        if isinstance(image, str):
            img = cv2.imread(image)
            if img is None:
                raise ValueError(f"Unable to read image from path: {image}")
        elif isinstance(image, np.ndarray):
            img = cv2.cvtColor(image, cv2.COLOR_RGB2BGR)
        else:
            raise ValueError("Unsupported image type")

        gray = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY)
        threshold_img = cv2.threshold(gray, 0, 255, cv2.THRESH_BINARY + cv2.THRESH_OTSU)[1]

        text = pytesseract.image_to_string(threshold_img, lang=lang)

        if isinstance(image, str):
            os.remove(image)

        results = annif.suggest(project_id=proj_ids[project_num], text=text)
        sorted_results = sorted(results, key=lambda x: x['score'], reverse=True)

        html_content = """
        <div id="suggestions-wrapper">
            <h2 id="suggestions">Suggested subjects</h2>
            <ul class="list-group" id="results">
        """

        for result in sorted_results:
            html_content += f"""
            <li class="list-group-item">
                <meter value="{result['score']}" min="0" max="1"></meter>
                <a href="{result['uri']}">{result['label']}</a>
            </li>
            """

        html_content += """
            </ul>
        </div>
        """

        return text, html_content
    except Exception as e:
        return str(e), ""

langs = ("eng", "fin", "swe")

css = """
.gradio-container, .gradio-container * {
    color: #343260 !important;
    background-color: #f3f3f6;
    color: #343260;
    font-family: Jost, sans-serif;
    font-weight: 400;
    font-size: 1.2rem;
    line-height: 1.2;
}
body, .mygrclass {
    background-color: #f3f3f6;
    color: #343260;
    font-family: Jost, sans-serif;
    font-weight: 400;
    font-size: 1.2rem;
    line-height: 1.2;
}
.container {
    max-width: 1140px;
    margin: 0 auto;
    padding: 0 15px;
}
h1, h1 a {
    font-weight: 500;
    font-size: 2rem;
    text-align: center;
}
h2 {
    font-weight: 500;
    font-size: 1.5rem;
    padding: 0.5rem 0;
}
#form {
    background: linear-gradient(to bottom, #ffffff 0%, #d9dfe3 1%, #f3f3f6 1%, #f3f3f6 99%, #d9dfe3 99%, #ffffff 100%);
    padding: 2rem 0;
}
.form-control {
    border-radius: 0px;
}
#get-suggestions {
    margin: 2rem 0;
    background-color: #6280dc;
    color: white;
    border: none;
    border-radius: 0px;
    padding-right: 3rem;
    background-image: url('static/img/arrow-white.svg');
    background-position: 97% center;
    background-repeat: no-repeat;
}
#suggestions-wrapper {
    background-color: #f3f3f6;
    padding: 1rem;
}
#suggestions {
    border-top: 1px solid #343260;
    padding-top: 0.5rem;
    text-transform: uppercase;
    font-size: 1.1rem;
}
.list-group-item {
    display: flex;
    align-items: center;
    padding: 5px 0;
    border-bottom: 1px solid #e0e0e0;
}
meter {
    width: 24px;
    margin-right: 10px;
}
meter::-webkit-meter-bar {
    background-color: #ccc;
}
meter::-webkit-meter-optimum-value {
    background: #6280dc;
}
"""

with gr.Blocks(theme=gr.themes.Default(radius_size="none"), css=css) as demo:

    gr.HTML("""
    <h1><a href="https://annif.org">Annif</a> demo with image/camera input and OCR</h1>
    """)

    with gr.Row():
        with gr.Column(scale=3):
            image_input = gr.Image(type="numpy", label="Input Image", elem_classes="mygrclass")
        with gr.Column(scale=1):
            project = gr.Dropdown(choices=proj_names, label="Project (vocabulary and language)", type="index", elem_classes="mygrclass", value=proj_names[2])
            lang = gr.Dropdown(choices=langs, label="Select Language for OCR", type="value", value="eng", elem_classes="mygrclass")
            submit_btn = gr.Button("Get suggestions", elem_id="get-suggestions", elem_classes="mygrclass")

    with gr.Row():
        with gr.Column(scale=3):
            text_output = gr.Textbox(label="Extracted Text", elem_classes="mygrclass")
        with gr.Column(scale=1):
            html_output = gr.HTML()

    submit_btn.click(process, inputs=[image_input, project, lang], outputs=[text_output, html_output])

demo.launch()