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  1. Dockerfile +3 -3
  2. README.md +38 -1
Dockerfile CHANGED
@@ -19,9 +19,9 @@ RUN [ "python", "-c", "import nltk; nltk.download('wordnet', download_dir='/usr/
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  #
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  COPY src /
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- # ---- Listen to port 5000
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  #
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- EXPOSE 5000
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  # ---- Define the working dir in the contener
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  #
@@ -29,4 +29,4 @@ WORKDIR /
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  # ---- Commande to start the app
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  # ----
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- CMD ["gunicorn", "--bind", "0.0.0.0:5000", "main:app"]
 
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  #
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  COPY src /
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+ # ---- Listen to port 7860
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  #
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+ EXPOSE 7860
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  # ---- Define the working dir in the contener
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  #
 
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  # ---- Commande to start the app
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  # ----
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+ CMD ["gunicorn", "--bind", "0.0.0.0:7860", "main:app"]
README.md CHANGED
@@ -8,4 +8,41 @@ pinned: false
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  license: mit
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  ---
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- Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  license: mit
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  ---
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+ # Sign Language Application
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+ ## Hugging Face Spaces Repository
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+ This Sign Language recognition application is deployed on Hugging Face Spaces using Docker:
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+ - **Hugging Face Spaces Repository**: [project-sign-language/Sign_language](https://huggingface.co/spaces/project-sign-language/Sign_language)
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+ ## GitHub Repository
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+ The source code for this application is also available on GitHub:
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+ - **GitHub Repository**: [ShaymaEssghaier/Sign_language](https://github.com/ShaymaEssghaier/Sign_language)
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+ ## Docker Repository
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+ The Docker image used to deploy this application is also available on Docker Hub:
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+ - **Docker Repository**: [remifigea/sign_language](https://hub.docker.com/r/remifigea/sign_language)
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+ ## Dockerfiles
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+ ### Dockerfile
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+ Use this Dockerfile to run the application in local development mode.
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+ To build and run the image locally:
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+ ```bash
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+ docker build -f Dockerfile -t my-app:local .
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+ docker run -p 5000:5000 my-app:local
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+ ```
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+ ### Dockerfile.production
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+ Use this Dockerfile to run the application in production mode. This is the one used on the Hugging Face Hub repository after renaming it to Dockerfile.
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+