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Con el entorno virtual activado, instala las dependencias necesarias para el proyecto:
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pip install -r requirements.txt
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Este comando instalar谩 todas las librer铆as especificadas en el archivo requirements.txt, que incluye Gradio, Torch, OpenCV y otras necesarias para la clasificaci贸n.
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4. Ejecutar la aplicaci贸n
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Con el entorno configurado y las dependencias instaladas, ejecuta la aplicaci贸n:
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python app.py
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Esto iniciar谩 un servidor de Gradio que mostrar谩 la interfaz para subir una imagen de granos de cacao y realizar la clasificaci贸n de niveles de fermentaci贸n.
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title: "Fermentation Level Classification for Cocoa Beans"
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emoji: "馃崼"
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colorFrom: "blue"
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colorTo: "green"
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sdk: "gradio"
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sdk_version: "3.14.0" # O la versi贸n actual de Gradio que est茅s usando
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app_file: "app.py"
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pinned: false
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---
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This application classifies the fermentation level of cocoa beans using YOLO object detection.
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The model used is YOLOv5, and the interface allows users to upload an image of cocoa beans and get a processed output showing detected objects. You can view the source code on GitHub using the button below.
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<center>
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<a href="https://github.com/kebincontreras/cocoa_beans_interfaces" target="_blank" style="text-decoration: none;">
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<button style="background-color: #007bff; color: white; padding: 10px 20px; border: none; border-radius: 5px; font-size: 16px;">GitHub</button>
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</a>
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</center>
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### Features:
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- Upload an image of cocoa beans.
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- Classify fermentation levels using YOLOv5.
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- View the detected objects in the processed image.
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