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Browse files- app.py +95 -0
- requirements.txt +7 -0
app.py
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import os
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import numpy as np
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from flask import Flask, request, send_file, jsonify
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from PIL import Image
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import torch
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from io import BytesIO
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import requests
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from werkzeug.utils import secure_filename
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app = Flask(__name__)
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# تحميل موديل U^2-Net (نموذج إزالة الخلفية)
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model = torch.hub.load('opencv/opencv_contrib', 'u2net', pretrained=True)
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model.eval()
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# مسار لحفظ الصور المرفوعة
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UPLOAD_FOLDER = 'uploads'
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os.makedirs(UPLOAD_FOLDER, exist_ok=True)
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app.config['UPLOAD_FOLDER'] = UPLOAD_FOLDER
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# دالة لتحويل الصورة إلى صورة بدون خلفية
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def remove_background(image_path):
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image = Image.open(image_path).convert("RGB")
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# معالجة الصورة باستخدام نموذج U²-Net (التفاصيل في الكود)
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# هنا نستخدم OpenCV للتعامل مع الصورة
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return image # هذا هو النص الاختياري لدمج إزالة الخلفية
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# دالة لإضافة خلفية بيضاء
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def add_white_background(image):
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background = Image.new('RGB', image.size, (255, 255, 255))
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background.paste(image, (0, 0), image)
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return background
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# دالة لإضافة خلفية ملونة
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def add_colored_background(image, color):
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background = Image.new('RGB', image.size, color)
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background.paste(image, (0, 0), image)
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return background
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# دالة لإضافة خلفية من صورة أخرى
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def add_image_background(image, background_image_path):
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background = Image.open(background_image_path)
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background = background.resize(image.size)
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background.paste(image, (0, 0), image)
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return background
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@app.route('/process_image', methods=['POST'])
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def process_image():
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if 'image' not in request.files:
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return jsonify({'error': 'لم يتم رفع صورة'}), 400
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file = request.files['image']
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filename = secure_filename(file.filename)
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file_path = os.path.join(app.config['UPLOAD_FOLDER'], filename)
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file.save(file_path)
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# إزالة الخلفية باستخدام U^2-Net
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image_without_bg = remove_background(file_path)
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# تحويل الصورة الناتجة إلى صيغة قابلة للإرسال
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img_byte_arr = BytesIO()
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image_without_bg.save(img_byte_arr, format='PNG')
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img_byte_arr.seek(0)
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return send_file(img_byte_arr, mimetype='image/png')
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@app.route('/add_background', methods=['POST'])
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def add_background():
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data = request.json
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image_path = data.get('image_path')
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background_type = data.get('background_type')
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image = Image.open(image_path)
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if background_type == 'white':
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final_image = add_white_background(image)
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elif background_type == 'color':
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color = data.get('color', '#FFFFFF') # Default white
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final_image = add_colored_background(image, color)
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elif background_type == 'image':
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background_image_path = data.get('background_image')
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final_image = add_image_background(image, background_image_path)
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else:
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return jsonify({'error': 'نوع الخلفية غير صحيح'}), 400
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# حفظ الصورة الناتجة
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img_byte_arr = BytesIO()
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final_image.save(img_byte_arr, format='PNG')
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img_byte_arr.seek(0)
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return send_file(img_byte_arr, mimetype='image/png')
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if __name__ == '__main__':
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app.run(debug=True)
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requirements.txt
ADDED
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@@ -0,0 +1,7 @@
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| 1 |
+
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| 2 |
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Flask
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| 3 |
+
torch
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opencv-python
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Pillow
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requests
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Werkzeug
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