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from functions import generate_text, get_diagnosis, summarize_text, text_to_speech, translate_fr_to_es
from predict import predict
from utils import load_image
from dotenv import load_dotenv
import streamlit as st
from layout import show_header, show_prediction_section, show_footer
from styles import inject_particles_js, inject_bootstrap_and_custom_css
# Configuration de la page
st.set_page_config(
page_title="Application Multitâche",
page_icon=":robot_face:",
layout="wide",
initial_sidebar_state="auto",
)
load_dotenv()
# Injecter les styles et scripts
inject_particles_js()
inject_bootstrap_and_custom_css()
# Charger les images
image_path = "images/tumor.png"
image_base64 = load_image(image_path)
linkedin_image_base64 = load_image("images/skill-icons--linkedin.svg")
github_image_base64 = load_image("images/skill-icons--github-dark.svg")
huggingface_image_base64 = load_image("images/Hugging_Face_idJ6-I79C__1.svg")
favicon_image_base64 = load_image("images/favicon.png")
# Afficher l'en-tête
show_header(favicon_image_base64, image_base64)
# Afficher la section de prédiction
show_prediction_section()
_, col2, col3, _ = st.columns([2, 6, 6, 2])
translation = None
with col2:
uploaded_file = st.file_uploader("Téléchargez une image de tumeur...", type=["jpg", "jpeg", "png"])
if uploaded_file:
_, col2, _ = st.columns([1, 3, 1])
with col2:
st.image(uploaded_file, caption="Image de tumeur", width=400)
button = st.button("Prédire", use_container_width=True)
if button:
st.spinner("Prédiction en cours...")
predicted, confidence = predict(uploaded_file)
diagnosis_prompt = get_diagnosis(predicted, confidence)
diagnosis = generate_text(diagnosis_prompt)
summary = summarize_text(diagnosis)
translation = translate_fr_to_es(summary)
output_path = text_to_speech(translation)
if uploaded_file and translation:
with col3:
st.markdown(
f"""
<div class="card border-0 shadow-sm p-4">
<div class="card-body">
<h2 class="gradient-text"> Resultat de la prédiction </h2>
<p class="lead"> {summary} </p>
<p class="lead"> {translation} </p
</div>
</div>
""",
unsafe_allow_html=True,
)
st.audio(output_path, format="audio/mp3")
# Afficher le pied de page
show_footer(linkedin_image_base64, github_image_base64, huggingface_image_base64) |