Update app.py
Browse files
app.py
CHANGED
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from flask import Flask, request, jsonify, render_template, send_file
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from flask_cors import CORS
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from PIL import Image
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import io
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import json
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import os
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import uuid
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import google.generativeai as genai
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import numpy as np
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generation_config = {
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}
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safety_settings = [
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]
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GOOGLE_API_KEY = os.environ.get("TOKEN")
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# Configuration de l'API Gemini
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genai.configure(api_key=GOOGLE_API_KEY)
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app = Flask(__name__)
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CORS(app)
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@app.route('/', methods=['GET'])
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def svt():
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"""Renders the SVT page."""
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return render_template("svt.html")
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# Prompt pour la détection d'objets
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DETECTION_PROMPT = "Detect items, with no more than 20 items. Output a json list where each entry contains the 2D bounding box in \"box_2d\" and a text label in \"label\"."
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@@ -68,7 +62,10 @@ UPLOAD_FOLDER = 'uploads'
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app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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@app.route('/analyze', methods=['POST'])
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def analyze_image():
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# 1. Détection d'objets avec Gemini
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model = genai.GenerativeModel("gemini-2.0-flash-exp",safety_settings=safety_settings,generation_config=generation_config)
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image_part = {
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"mime_type": "image/jpeg",
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"data": open(filename, "rb").read()
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}
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response = model.generate_content([DETECTION_PROMPT, image_part])
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print(f"Une erreur s'est produite : {e}")
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return jsonify({'error': f'Erreur lors du traitement de l\'image : {e}'}), 500
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@app.route('/uploads/<filename>')
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def uploaded_file(filename):
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return send_file(os.path.join(app.config['UPLOAD_FOLDER'], filename))
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from flask import Flask, request, jsonify, render_template, send_file
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from flask_cors import CORS
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from PIL import Image, ImageDraw
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import io
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import json
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import os
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import uuid
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import google.generativeai as genai
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# Configuration de l'API Gemini
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generation_config = {
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"temperature": 1,
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"max_output_tokens": 8192,
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}
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safety_settings = [
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{
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"category": "HARM_CATEGORY_HARASSMENT",
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"threshold": "BLOCK_NONE"
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},
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{
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"category": "HARM_CATEGORY_HATE_SPEECH",
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"threshold": "BLOCK_NONE"
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},
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{
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"category": "HARM_CATEGORY_SEXUALLY_EXPLICIT",
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"threshold": "BLOCK_NONE"
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},
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{
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"category": "HARM_CATEGORY_DANGEROUS_CONTENT",
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"threshold": "BLOCK_NONE"
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},
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]
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GOOGLE_API_KEY = os.environ.get("TOKEN") # Assurez vous que la variable d'environnement TOKEN est bien définie
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genai.configure(api_key=GOOGLE_API_KEY)
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app = Flask(__name__)
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CORS(app)
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# Prompt pour la détection d'objets
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DETECTION_PROMPT = "Detect items, with no more than 20 items. Output a json list where each entry contains the 2D bounding box in \"box_2d\" and a text label in \"label\"."
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app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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@app.route('/', methods=['GET'])
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def svt():
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"""Renders the SVT page."""
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return render_template("templates_svt (3).html")
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@app.route('/analyze', methods=['POST'])
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def analyze_image():
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# 1. Détection d'objets avec Gemini
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model = genai.GenerativeModel("gemini-2.0-flash-exp",safety_settings=safety_settings,generation_config=generation_config)
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image_part = {
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"mime_type": "image/jpeg",
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"data": open(filename, "rb").read()
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}
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response = model.generate_content([DETECTION_PROMPT, image_part])
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print(f"Une erreur s'est produite : {e}")
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return jsonify({'error': f'Erreur lors du traitement de l\'image : {e}'}), 500
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# Servir les fichiers statiques depuis le dossier 'uploads'
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@app.route('/uploads/<filename>')
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def uploaded_file(filename):
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return send_file(os.path.join(app.config['UPLOAD_FOLDER'], filename))
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