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| from flask import Flask, request, jsonify | |
| import cv2 | |
| import numpy as np | |
| from sign_language_model import predict_sign_language | |
| app = Flask(__name__) | |
| def home(): | |
| return "Welcome to the Learning App for Deaf and Mute" | |
| def convert_sign_to_text(): | |
| """ | |
| Accepts an image of a sign language gesture and converts it to text. | |
| """ | |
| try: | |
| file = request.files['image'] | |
| image = cv2.imdecode(np.fromstring(file.read(), np.uint8), cv2.IMREAD_COLOR) | |
| text = predict_sign_language(image) | |
| return jsonify({"text": text, "status": "success"}), 200 | |
| except Exception as e: | |
| return jsonify({"error": str(e), "status": "failure"}), 500 | |
| def learning_module(): | |
| """ | |
| Provides learning content for deaf and mute individuals. | |
| """ | |
| # Example learning content (can be extended) | |
| content = { | |
| "title": "Learn Sign Language", | |
| "lessons": [ | |
| {"id": 1, "title": "Alphabet A-Z"}, | |
| {"id": 2, "title": "Common Words and Phrases"}, | |
| {"id": 3, "title": "Numbers 1-10"} | |
| ] | |
| } | |
| return jsonify(content), 200 | |
| if __name__ == '__main__': | |
| app.run(debug=True) |