Object Tales generates stories based on the objects in the images. It uses YOLOv3-320 to detect objects and GPT-2 to generate stories. This is a Python 3.8 application.
git clone https://github.com/Rexaintreal/object-tales.git
cd object-tales/pip install -r requirements.txtDownload the pre-trained YOLOv3-320 weights from the official repository using the following command:
wget https://pjreddie.com/media/files/yolov3.weights -O models/yolov3-320.weightsDownload the GPT-2 model from OpenAI using the following command:
python download_model.py 117MTo use the Object Tales GUI application, follow these steps:
- Launch the application by running the
main.pyfile. - Click the "Open Image" button to select an image to generate a story for.
- Click the "Generate Story" button to generate a story based on the objects detected in the selected image.
- The generated story will be displayed in the "Story" section of the application.
Note: Make sure that the required dependencies are installed before launching the application. See the "Installation" section for details.
Object Tales is a Python-based application that generates stories based on the objects in the images. It uses a combination of YOLOv3-320 object detection and GPT-2 text generation to analyze the images and create unique and engaging narratives.
When you run the program, you can select an image from your local file system or use the program's built-in camera to capture an image. Object Tales then uses YOLOv3-320 to identify the objects in the image and extract their features. These features are then passed to GPT-2, which generates a story based on the objects and their attributes.
The program outputs the generated story to the screen, and you can save it to a file if desired. Object Tales also allows you to adjust the length and complexity of the generated stories, as well as the confidence threshold for object detection.
Overall, Object Tales provides a fun and creative way to explore the stories hidden in everyday objects and images.
Object Tales was created by Saurabh Tiwari.
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