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Commit 16066790 authored by Simon Majorczyk's avatar Simon Majorczyk
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Changement CSS

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app_glob.py 0 → 100644
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View file @ 16066790
from flask import Flask, request, jsonify, render_template
import pickle
import pandas as pd
from sklearn.preprocessing import StandardScaler
import numpy as np
app = Flask(__name__)
# Charger le modèle
with open('random_forest_model_binaire.pkl', 'rb') as model_file:
rf = pickle.load(model_file)
# Charger le scaler entraîné
with open('scaler_binaire.pkl', 'rb') as scaler_file:
scaler = pickle.load(scaler_file)
@app.route('/')
def home():
return render_template('index-glob.html')
@app.route('/predict', methods=['POST'])
def predict():
return process_prediction(request.form, '/predict')
@app.route('/predict_sup0', methods=['POST'])
def predict_sup0():
return process_prediction(request.form, '/predict_sup0')
def process_prediction(form_data, endpoint):
data = form_data.to_dict()
if 'name' in data:
data['nb_caracteres_sans_espaces'] = len(data['name'].replace(" ", ""))
if 'artists' in data:
data['nb_artistes'] = data['artists'].count(',') + 1
data['featuring'] = int(data['nb_artistes'] > 1)
if 'duration_ms' in data:
duration_ms = float(data['duration_ms'])
data['duree_minute'] = float(f"{int(duration_ms // 60000)}.{int((duration_ms % 60000) // 1000):02d}")
if 'year' in data:
year = int(data['year'])
data['categorie_annee'] = 3 if year < 1954 else 2 if year < 2002 else 1
if 'tempo' in data:
tempo = float(data['tempo'])
if 40 <= tempo < 60:
data['categorie_tempo'] = 1
elif 60 <= tempo < 66:
data['categorie_tempo'] = 2
elif 66 <= tempo < 76:
data['categorie_tempo'] = 3
elif 76 <= tempo < 108:
data['categorie_tempo'] = 4
elif 108 <= tempo < 120:
data['categorie_tempo'] = 5
elif 120 <= tempo < 163:
data['categorie_tempo'] = 6
elif 163 <= tempo < 200:
data['categorie_tempo'] = 7
elif 200 <= tempo <= 208:
data['categorie_tempo'] = 8
else:
data['categorie_tempo'] = 9
# Supprimer les clés non utilisées directement
data.pop('name', None)
data.pop('artists', None)
data.pop('duration_ms', None)
# Convertir les valeurs en float si possible
for key in data:
try:
data[key] = float(data[key])
except ValueError:
pass
expected_features = ['year', 'acousticness', 'danceability', 'energy', 'explicit',
'instrumentalness', 'key', 'liveness', 'loudness', 'mode',
'speechiness', 'tempo', 'valence', 'nb_caracteres_sans_espaces',
'nb_artistes', 'featuring', 'duree_minute', 'categorie_annee', 'categorie_tempo']
input_data = pd.DataFrame([[data.get(key, 0) for key in expected_features]], columns=expected_features)
missing_cols = [col for col in expected_features if col not in input_data.columns]
if missing_cols:
return jsonify({'error': f'Missing features: {missing_cols}'}), 400
input_data_scaled = scaler.transform(input_data)
predictions = rf.predict(input_data_scaled)
return jsonify({'predictions': int(predictions[0])})
if __name__ == '__main__':
app.run(debug=True)
spotify-popularity-prediction-v2/app_glob.py 0 → 100644
+ 94
− 0
View file @ 16066790
from flask import Flask, request, jsonify, render_template
import pickle
import pandas as pd
from sklearn.preprocessing import StandardScaler
import numpy as np
app = Flask(__name__)
# Charger le modèle
with open('random_forest_model_binaire.pkl', 'rb') as model_file:
rf = pickle.load(model_file)
# Charger le scaler entraîné
with open('scaler_binaire.pkl', 'rb') as scaler_file:
scaler = pickle.load(scaler_file)
@app.route('/')
def home():
return render_template('index-glob.html')
@app.route('/predict', methods=['POST'])
def predict():
# Récupérer les données du formulaire
data = request.form.to_dict()
# Calculer automatiquement les features
if 'name' in data:
data['nb_caracteres_sans_espaces'] = len(data['name'].replace(" ", ""))
if 'artists' in data:
data['nb_artistes'] = data['artists'].count(',') + 1
data['featuring'] = int(data['nb_artistes'] > 1)
if 'duration_ms' in data:
duration_ms = float(data['duration_ms'])
data['duree_minute'] = float(f"{int(duration_ms // 60000)}.{int((duration_ms % 60000) // 1000):02d}")
if 'year' in data:
year = int(data['year'])
data['categorie_annee'] = 3 if year < 1954 else 2 if year < 2002 else 1
if 'tempo' in data:
tempo = float(data['tempo'])
if 40 <= tempo < 60:
data['categorie_tempo'] = 1
elif 60 <= tempo < 66:
data['categorie_tempo'] = 2
elif 66 <= tempo < 76:
data['categorie_tempo'] = 3
elif 76 <= tempo < 108:
data['categorie_tempo'] = 4
elif 108 <= tempo < 120:
data['categorie_tempo'] = 5
elif 120 <= tempo < 163:
data['categorie_tempo'] = 6
elif 163 <= tempo < 200:
data['categorie_tempo'] = 7
elif 200 <= tempo <= 208:
data['categorie_tempo'] = 8
else:
data['categorie_tempo'] = 9
# Supprimer les clés non utilisées directement
data.pop('name', None)
data.pop('artists', None)
data.pop('duration_ms', None)
# Convertir les valeurs en float si possible
for key in data:
try:
data[key] = float(data[key])
except ValueError:
pass # Garder les valeurs non convertibles (ex: texte)
# Liste des features dans le bon ordre (comme lors de l'entraînement)
expected_features = ['year', 'acousticness', 'danceability', 'energy', 'explicit',
'instrumentalness', 'key', 'liveness', 'loudness', 'mode',
'speechiness', 'tempo', 'valence', 'nb_caracteres_sans_espaces',
'nb_artistes', 'featuring', 'duree_minute', 'categorie_annee', 'categorie_tempo']
# S'assurer que les colonnes du DataFrame correspondent à celles du modèle, dans le bon ordre
input_data = pd.DataFrame([[data.get(key, 0) for key in expected_features]], columns=expected_features)
# Vérifier que toutes les colonnes attendues sont présentes
missing_cols = [col for col in expected_features if col not in input_data.columns]
if missing_cols:
return jsonify({'error': f'Missing features: {missing_cols}'}), 400
# Normalisation des features
input_data_scaled = scaler.transform(input_data)
# Prédiction
predictions = rf.predict(input_data_scaled)
return jsonify({'predictions': int(predictions[0])})
if __name__ == '__main__':
app.run(debug=True)
templates/index-glob.html 0 → 100644
+ 225
− 0
View file @ 16066790
<!DOCTYPE html>
<html lang="fr">
<head>
<meta charset="UTF-8">
<meta name="viewport" content="width=device-width, initial-scale=1.0">
<title>Prédiction de Popularité</title>
<style>
body {
font-family: Arial, sans-serif;
margin: 0;
display: flex;
}
/* Sidebar */
.sidebar {
width: 200px;
background-color: #333;
color: white;
height: 100vh;
padding-top: 20px;
display: flex;
flex-direction: column;
align-items: center;
}
.sidebar button {
width: 80%;
padding: 10px;
margin: 10px 0;
border: none;
background: #444;
color: white;
cursor: pointer;
font-size: 16px;
text-align: center;
}
.sidebar button:hover {
background: #555;
}
.content {
flex-grow: 1;
padding: 20px;
}
/* Cacher les sections par défaut */
.tab-content {
display: none;
}
.active {
display: block;
}
form {
max-width: 600px;
margin: auto;
}
label {
display: block;
margin-top: 10px;
font-weight: bold;
}
input[type="text"], input[type="number"] {
width: 100%;
padding: 8px;
margin-top: 5px;
border: 1px solid #ccc;
border-radius: 4px;
}
button {
margin-top: 20px;
padding: 10px 20px;
background-color: #4CAF50;
color: white;
border: none;
border-radius: 4px;
cursor: pointer;
}
button:hover {
background-color: #45a049;
}
#result {
margin-top: 20px;
font-size: 1.2em;
color: #555;
}
</style>
</head>
<body>
<!-- Sidebar pour naviguer entre les onglets -->
<div class="sidebar">
<button onclick="showTab('tab1')">Prédiction Standard</button>
<button onclick="showTab('tab2')">Prédiction (>0)</button>
</div>
<!-- Contenu principal -->
<div class="content">
<h1>Prédire la Popularité</h1>
<!-- Formulaire 1 : Prédiction Standard -->
<div id="tab1" class="tab-content active">
<form id="predictionForm">
<label for="name">Titre de la chanson :</label>
<input type="text" id="name" name="name" required>
<label for="year">Année (Sous format YYYY):</label>
<input type="number" step="0.0001" id="year" name="year" required>
<label for="acousticness">Acousticness (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="acousticness" name="acousticness" required>
<label for="danceability">Danceability (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="danceability" name="danceability" required>
<label for="energy">Energy (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="energy" name="energy" required>
<label for="explicit">Explicit (0 ou 1 en entier):</label>
<input type="number" id="explicit" name="explicit" required>
<label for="instrumentalness">Instrumentalness (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="instrumentalness" name="instrumentalness" required>
<label for="key">Key (0 à 11 en chiffre entier):</label>
<input type="number" id="key" name="key" required>
<label for="liveness">Liveness (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="liveness" name="liveness" required>
<label for="loudness">Loudness (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="loudness" name="loudness" required>
<label for="mode">Mode (0 ou 1 en entier):</label>
<input type="number" id="mode" name="mode" required>
<label for="speechiness">Speechiness (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="speechiness" name="speechiness" required>
<label for="tempo">Tempo (Sous format d'un nombre décimal jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="tempo" name="tempo" required>
<label for="valence">Valence (0 à 1 jusqu'à 4 chiffres après la virgule):</label>
<input type="number" step="0.0001" id="valence" name="valence" required>
<button type="button" onclick="sendPrediction('/predict')">Prédire</button>
</form>
</div>
<!-- Formulaire 2 : Prédiction (>0) -->
<div id="tab2" class="tab-content">
<form id="predictionFormSup0">
<label for="name">Titre de la chanson :</label>
<input type="text" id="name" name="name" required>
<label for="year">Année :</label>
<input type="number" id="year" name="year" required>
<label for="acousticness">Acousticness :</label>
<input type="number" step="0.0001" id="acousticness" name="acousticness" required>
<label for="danceability">Danceability :</label>
<input type="number" step="0.0001" id="danceability" name="danceability" required>
<label for="energy">Energy :</label>
<input type="number" step="0.0001" id="energy" name="energy" required>
<label for="explicit">Explicit (0 ou 1) :</label>
<input type="number" id="explicit" name="explicit" required>
<label for="instrumentalness">Instrumentalness :</label>
<input type="number" step="0.0001" id="instrumentalness" name="instrumentalness" required>
<label for="key">Key :</label>
<input type="number" id="key" name="key" required>
<label for="liveness">Liveness :</label>
<input type="number" step="0.0001" id="liveness" name="liveness" required>
<label for="loudness">Loudness :</label>
<input type="number" step="0.0001" id="loudness" name="loudness" required>
<label for="mode">Mode :</label>
<input type="number" id="mode" name="mode" required>
<label for="speechiness">Speechiness :</label>
<input type="number" step="0.0001" id="speechiness" name="speechiness" required>
<label for="tempo">Tempo :</label>
<input type="number" step="0.0001" id="tempo" name="tempo" required>
<label for="valence">Valence :</label>
<input type="number" step="0.0001" id="valence" name="valence" required>
<button type="button" onclick="sendPrediction('/predict_sup0', 'predictionFormSup0')">Prédire (>0)</button>
</form>
</div>
<div id="result"></div>
</div>
<script>
// Fonction pour afficher un onglet et cacher l'autre
function showTab(tabId) {
document.querySelectorAll('.tab-content').forEach(tab => {
tab.style.display = "none";
});
document.getElementById(tabId).style.display = "block";
}
// Fonction pour envoyer la requête au bon endpoint
async function sendPrediction(endpoint, formId = "predictionForm") {
const form = document.getElementById(formId);
const formData = new FormData(form);
const response = await fetch(endpoint, {
method: "POST",
body: formData
});
const result = await response.json();
document.getElementById("result").innerText = `Prédiction: ${result.predictions}`;
}
// Afficher l'onglet par défaut
showTab('tab1');
</script>
</body>
</html>
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