app_version/v1_app.py

from flask import Flask, request, render_template, jsonify, send_from_directory
import os
import torch
import numpy as np
import cv2
from segment_anything import sam_model_registry, SamPredictor
from werkzeug.utils import secure_filename
import warnings

# Initialisation de Flask
app = Flask(
    __name__,
    template_folder='templates',  # Chemin des fichiers HTML
    static_folder='static'       # Chemin des fichiers statiques
)
app.config['UPLOAD_FOLDER'] = os.path.join('static', 'uploads')
os.makedirs(app.config['UPLOAD_FOLDER'], exist_ok=True)

# Charger le modèle SAM
MODEL_TYPE = "vit_b"
MODEL_PATH = os.path.join('models', 'sam_vit_b_01ec64.pth')
device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')

print("Chargement du modèle SAM...")
try:
    state_dict = torch.load(MODEL_PATH, map_location="cpu", weights_only=True)
except TypeError:
    with warnings.catch_warnings():
        warnings.simplefilter("ignore", category=UserWarning)
        state_dict = torch.load(MODEL_PATH, map_location="cpu")

# Initialiser et charger le modèle
sam = sam_model_registry[MODEL_TYPE]()
sam.load_state_dict(state_dict, strict=False)
sam.to(device=device)
predictor = SamPredictor(sam)
print("Modèle SAM chargé avec succès!")


@app.route('/', methods=['GET', 'POST'])
def index():
    if request.method == 'POST':
        if 'image' not in request.files:
            return "Aucun fichier sélectionné", 400
        file = request.files['image']
        if file.filename == '':
            return "Nom de fichier vide", 400
        filename = secure_filename(file.filename)
        filepath = os.path.join(app.config['UPLOAD_FOLDER'], filename)
        file.save(filepath)
        # Passer le nom du fichier au template pour affichage
        return render_template('index.html', uploaded_image=filename)
    return render_template('index.html')


@app.route('/uploads/<filename>')
def uploaded_file(filename):
    return send_from_directory(app.config['UPLOAD_FOLDER'], filename)


if __name__ == '__main__':
    app.run(debug=True, host='0.0.0.0', port=5000)