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| license: apache-2.0 | |
| title: image-text-storyteller | |
| sdk: streamlit | |
| emoji: ⚡ | |
| colorFrom: purple | |
| colorTo: indigo | |
| pinned: true | |
| https://github.com/arjunprakash027/Story_Teller/assets/72484657/1c756dd8-9889-420d-a30e-13dbe137a2f0 | |
| # Story Teller | |
| Story Teller is a Streamlit application that generates a story based on an input image. It utilizes the Hugging Face Transformers library and the Salesforce BLIP Image Captioning model. | |
| ## Table of Contents | |
| - [Installation](#installation) | |
| - [Usage](#usage) | |
| - [API Token](#api-token) | |
| - [Models](#models) | |
| - [Running the Application](#running-the-application) | |
| - [Contributing](#contributing) | |
| ## Installation | |
| To install the necessary dependencies, run the following command: | |
| ```shell | |
| pip install -r requirements.txt | |
| ``` | |
| Make sure you have the required dependencies specified in the `requirements.txt` file. | |
| ## Usage | |
| To use the application, follow the steps below: | |
| 1. Run the Streamlit application by executing the following command: | |
| ```shell | |
| streamlit run app.py | |
| ``` | |
| 2. Access the application through the provided URL in the console. | |
| 3. The application interface will appear with the title "Story Teller" and an instruction to "Upload an image and get a story". | |
| 4. Click on the "Upload your file here..." button to select an image file (supported formats: PNG, JPEG, JPG). | |
| 5. Once the image is uploaded, it will be displayed on the page. | |
| 6. The application will process the uploaded image using the Salesforce BLIP Image Captioning model and generate a textual description of the image. | |
| 7. The generated text will then be passed to the Hugging Face API to generate a story based on the text. | |
| 8. The application will display the generated story on the page. | |
| 9. If any errors occur during the process, an error message will be shown on the page, and you can try again. | |
| ## API Token | |
| The application requires an API token from Hugging Face to access the story generation model. To obtain an API token, follow these steps: | |
| 1. Sign up or log in to your Hugging Face account at [https://huggingface.co/](https://huggingface.co/). | |
| 2. Once logged in, go to your account settings and navigate to the "API token" section. | |
| 3. Generate a new API token, copy it, and replace the `"your api key"` placeholder in the `Models` class of `text_model.py` with your actual API token. | |
| ## Models | |
| The `Models` class in `text_model.py` encapsulates the functionality of the application. It contains the following methods: | |
| - `__init__()`: | |
| - Initializes the class and sets the API token and model ID. | |
| - `img2text(url)`: | |
| - Takes an image URL as input and uses the Salesforce BLIP Image Captioning model to convert the image into text. It returns the generated text. | |
| - `story(payload)`: | |
| - Takes a payload as input, which contains the generated text, and sends a request to the Hugging Face API to generate a story based on the text. It returns the generated story. | |
| - `chain(payload, num=0)`: | |
| - This method acts as a recursive function that generates a chain of stories. It takes a payload as input, which initially contains the generated text. It recursively calls the `story()` method and updates the payload until the desired number of stories (50 in this case) is generated. The progress bar is also updated accordingly. | |
| ## Running the Application | |
| If you are curious and want to just try the backend models | |
| execute the following command: | |
| ```shell | |
| python text_model.py | |
| ``` | |
| Make sure you have the required dependencies installed, as mentioned in the installation section. | |
| ## Contributing | |
| Contributions to the Story Teller application are welcome! If you find any issues or have suggestions for improvements, please feel free to open an issue or submit a pull request. |