import streamlit as st
import pandas as pd
import ast
import numpy as np
from PIL import Image, ImageDraw, ImageFont

df = pd.read_excel("sample_dfver3.xlsx")
print(df)
image_names = df['filename_gs'].unique().tolist()
default_font = ImageFont.load_default()
#@st.cache
def process_image(image_name, confidence):
    rows = df[df['filename_gs'] == image_name]
    image_path = image_name
    image = Image.open(image_path)
    draw = ImageDraw.Draw(image)
    
    for _, row in rows.iterrows():
        bbox_str = row['bbox']
        bbox = ast.literal_eval(bbox_str)
        confidence_value = row['conf']
        common_name = row['common_name']
        
        x = round(float(bbox[0]) * image.width)
        y = round(float(bbox[1]) * image.height)
        w = round(float(bbox[2]) * image.width)
        h = round(float(bbox[3]) * image.height)
        
        if confidence_value >= float(confidence):
            draw.rectangle([(x, y), (x+w, y+h)], outline=(0, 255, 0), width=5)
            
            text = f"{common_name} : {confidence_value:.3f}"
            text_width, text_height = draw.textsize(text, font=default_font)
            
            text_x = x
            text_y = y - text_height - 10
            
            bbox = (text_x, text_y, text_x + text_width, text_y + text_height)
            draw.rectangle(bbox, fill="red")
            draw.text((text_x, text_y), text, fill="#FFFFFF", font=default_font)
    
    return np.array(image)

def main():
    st.title("Bounding Box Visualization")
    st.sidebar.header("Settings")
    confidence = st.sidebar.slider("Confidence", min_value=0.0, max_value=1.0, step=0.01)
    image_name = st.sidebar.selectbox("Select an image", image_names)
    
    image = process_image(image_name, confidence)
    st.image(image, use_column_width=True)

if __name__ == "__main__":
    main()