| Name | lsvtest JSON |
| Version |
0.0.3
JSON |
| download |
| home_page | None |
| Summary | Recognize up to 10 signs of the LSV (Venezuelan Sign Language) |
| upload_time | 2024-05-12 19:28:35 |
| maintainer | None |
| docs_url | None |
| author | None |
| requires_python | >=3.8 |
| license | MIT License Copyright (c) 2024 Carlos Bone Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. |
| keywords |
opencv
mediapipe holistic
ml
lsv
|
| VCS |
 |
| bugtrack_url |
|
| requirements |
No requirements were recorded.
|
| Travis-CI |
No Travis.
|
| coveralls test coverage |
No coveralls.
|
# lsvtest
lsvtest es un paquete Python que proporciona funcionalidades para la detección y reconocimiento de LSV (Lenguaje de Señas Venezolano).
## Instalación
Puedes instalar `lsvtest` utilizando pip:
```bash
pip install lsvtest
```
Uso
Para usar lsvtest, sigue estos pasos:
Crear una estructura de proyectoCrea una estructura de proyecto como la siguiente:
```
project/
│
├── main.py
└── script.py
```
Contenido de main.py
```python
from flask import Flask, jsonify
import subprocess
app = Flask(__name__)
# Variable to keep track of the process
process = None
@app.route("/start", methods=["GET"])
def start_process():
global process
if process is None:
# Replace 'your_command_here' with the command you want to run
process = subprocess.Popen(
[
"python",
"-c",
'import sys; sys.path.append("."); import script; script.start()',
]
)
return jsonify({"status": "Process started"}), 200
else:
return jsonify({"status": "Process is already running"}), 200
@app.route("/stop", methods=["GET"])
def stop_process():
global process
if process is not None:
process.terminate() # Sends SIGTERM
process = None
return jsonify({"status": "Process stopped"}), 200
else:
return jsonify({"status": "No process is running"}), 200
if __name__ == "__main__":
app.run(debug=True, port=5000)
```
Contenido de script.py
```python
from lsvtest import LSVRecognition
def start():
recognition_service = LSVRecognition()
recognition_service.continuous_detection(
source=0,
output=lambda token: print(token),
wsl_compatibility=True,
show_video=True
)
```
Ejecuta el servidor Flask desde la terminal en la carpeta del proyecto:
```bash
python main.py
```
Envía una solicitud GET a http://localhost:5000/start para iniciar el proceso de reconocimiento.
Envía una solicitud GET a http://localhost:5000/stop para detener el proceso de reconocimiento.
Puedes personalizar el reconocimiento modificando los parámetros de continuous_detection en script.py.
## Problemas al instalar
Si tienes problemas al momento de instalar el paquete, prueba ejecutar primero:
```bash
pip install mediapipe opencv-python scikit-learn tensorflow
```
Y luego prueba a instalar el paquete nuevamente
Raw data
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"description": "# lsvtest\n\nlsvtest es un paquete Python que proporciona funcionalidades para la detecci\u00f3n y reconocimiento de LSV (Lenguaje de Se\u00f1as Venezolano).\n\n## Instalaci\u00f3n\n\nPuedes instalar `lsvtest` utilizando pip:\n\n```bash\npip install lsvtest\n```\n\nUso\nPara usar lsvtest, sigue estos pasos:\n\nCrear una estructura de proyectoCrea una estructura de proyecto como la siguiente:\n\n```\nproject/\n\u2502\n\u251c\u2500\u2500 main.py\n\u2514\u2500\u2500 script.py\n```\n\nContenido de main.py\n\n```python\nfrom flask import Flask, jsonify\nimport subprocess\n\napp = Flask(__name__)\n\n# Variable to keep track of the process\nprocess = None\n\n@app.route(\"/start\", methods=[\"GET\"])\ndef start_process():\n global process\n if process is None:\n # Replace 'your_command_here' with the command you want to run\n process = subprocess.Popen(\n [\n \"python\",\n \"-c\",\n 'import sys; sys.path.append(\".\"); import script; script.start()',\n ]\n )\n return jsonify({\"status\": \"Process started\"}), 200\n else:\n return jsonify({\"status\": \"Process is already running\"}), 200\n\n@app.route(\"/stop\", methods=[\"GET\"])\ndef stop_process():\n global process\n if process is not None:\n process.terminate() # Sends SIGTERM\n process = None\n return jsonify({\"status\": \"Process stopped\"}), 200\n else:\n return jsonify({\"status\": \"No process is running\"}), 200\n\nif __name__ == \"__main__\":\n app.run(debug=True, port=5000)\n```\n\nContenido de script.py\n\n```python\nfrom lsvtest import LSVRecognition\n\ndef start():\n recognition_service = LSVRecognition()\n\n recognition_service.continuous_detection(\n source=0, \n output=lambda token: print(token), \n wsl_compatibility=True, \n show_video=True\n )\n```\n\nEjecuta el servidor Flask desde la terminal en la carpeta del proyecto:\n```bash\npython main.py\n```\n\nEnv\u00eda una solicitud GET a http://localhost:5000/start para iniciar el proceso de reconocimiento.\n\nEnv\u00eda una solicitud GET a http://localhost:5000/stop para detener el proceso de reconocimiento.\n\nPuedes personalizar el reconocimiento modificando los par\u00e1metros de continuous_detection en script.py.\n\n## Problemas al instalar\n\nSi tienes problemas al momento de instalar el paquete, prueba ejecutar primero:\n\n```bash\npip install mediapipe opencv-python scikit-learn tensorflow \n```\n\nY luego prueba a instalar el paquete nuevamente\n",
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