import gradio as gr
import numpy as np
import pandas as pd
from app_utils import annotate_planogram_compliance, do_sorting, xml_to_csv
from inference import run
import json
import os
from tempfile import NamedTemporaryFile


# Target names list
target_names = [
    "Bottle,100PLUS ACTIVE 1.5L",
    "Bottle,100PLUS ACTIVE 500ML",
    "Bottle,100PLUS LEMON LIME 1.5L",
    # Add all other target names here
]

# Define the function to run planogram compliance check
def planogram_compliance_check(planogram_image, master_planogram_image, annotation_file):
    # Convert uploaded images to numpy arrays
    planogram_img = np.array(planogram_image)
    master_planogram_img = np.array(master_planogram_image)

    # Perform inference on planogram image
    result_list = run(
        weights="base_line_best_model_exp5.pt",
        source=planogram_img,
        imgsz=[640, 640],
        conf_thres=0.6,
        iou_thres=0.6,
    )

    # Load annotation file and convert to DataFrame
    if annotation_file is not None:
        annotation_df = xml_to_csv(annotation_file)
        sorted_xml_df = do_sorting(annotation_df)
    else:
        sorted_xml_df = None

    # Run planogram compliance check
    compliance_score, annotated_image = run_compliance_check(
        planogram_img, master_planogram_img, sorted_xml_df, result_list
    )

    return compliance_score, annotated_image

# Define the function to run planogram compliance check
def run_compliance_check(planogram_img, master_planogram_img, sorted_xml_df, result_list):
    # Perform further processing and calculation of compliance score
    compliance_score = 0.0  # Placeholder for actual score calculation
    annotated_image = None  # Placeholder for annotated image

    # Your compliance score calculation and image annotation logic here

    return compliance_score, annotated_image

# Gradio interface
planogram_check_interface = gr.Interface(
    fn=planogram_compliance_check,
    inputs=[
        gr.inputs.Image(label="Planogram Image"),
        gr.inputs.Image(label="Master Planogram Image"),
        gr.inputs.Dataframe(label="Annotation File (XML)")
    ],
    outputs=[
        gr.outputs.Textbox(label="Compliance Score"),
        gr.outputs.Image(label="Annotated Planogram Image"),
    ],
    title="Planogram Compliance Checker",
    description="Upload planogram image, master planogram image, and annotation file (if available) to check compliance."
)

# Launch the interface
planogram_check_interface.launch()