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--- |
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language: |
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- en |
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tags: |
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- image-classification |
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- font-detection |
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- resnet |
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- fine-tuning |
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datasets: |
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- custom |
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license: mit |
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library_name: transformers |
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base_model: resnet-18 |
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--- |
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# Comic Sans Detector |
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This repository contains a fine-tuned ResNet-18 model, specifically trained to detect whether an image contains Comic Sans font. It is a fine-tuning of a previously fine-tuned font classification model, based on the ResNet-18 foundation model. |
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## Features |
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- Distinguishes between Comic Sans and non-Comic Sans images. |
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- Built using a custom dataset with two classes: `comic` and `not-comic`. |
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## Usage |
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To use this model with the Hugging Face Inference API: |
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```python |
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from transformers import pipeline |
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classifier = pipeline("image-classification", model="shoni/comic-sans-detector") |
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result = classifier("path/to/image.jpg") |
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print(result) |
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# Comic Sans Detector |
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This repository contains a fine-tuned ResNet-18 model, specifically trained to detect whether an image contains Comic Sans font. It is a fine-tuning of a previously fine-tuned font classification model, based on the ResNet-18 foundation model. |
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## Repository Contents |
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- **`comic-detector.ipynb`**: A notebook that demonstrates the training and evaluation process for the Comic Sans detector using the fine-tuned ResNet-18 model. |
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- **`image-format-generalizer.ipynb`**: A utility notebook for preparing and normalizing image datasets, ensuring consistent formatting across `/data` folders. |
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## Dataset Structure (Not Included) |
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The dataset used for training and evaluation should follow this structure: |
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``` |
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/data |
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├── comic/ |
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│ ├── image1.jpg |
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│ ├── image2.png |
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│ └── ... |
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├── not-comic/ |
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│ ├── image1.jpg |
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│ ├── image2.png |
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│ └── ... |
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``` |
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- **`comic/`**: Contains images labeled as featuring Comic Sans font. |
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- **`not-comic/`**: Contains images labeled as not featuring Comic Sans font. |
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⚠️ The dataset itself is not included in this repository. You must prepare and structure your dataset as described. |
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## How to Use |
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### 1. Clone the Repository |
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```bash |
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git clone https://huggingface.co/shoni/comic-sans-detector |
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cd comic-sans-detector |
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``` |
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### 2. Prepare the Dataset |
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Ensure your dataset is properly structured under a `/data` directory with `comic/` and `not-comic/` folders. |
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### 3. Run the Training Notebook |
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Open `comic-detector.ipynb` in Jupyter Notebook or an equivalent environment to retrain the model or evaluate it. |
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### 4. Format Images (Optional) |
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If your dataset images are not in a consistent format, use `image-format-generalizer.ipynb` to preprocess them. |
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## Model Usage |
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The fine-tuned model can be deployed directly via the Hugging Face Inference API. Once uploaded, the model can be used to classify whether an image contains Comic Sans font. |
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Example API usage (replace `shoni/comic-sans-detector` with your repository name): |
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```python |
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from transformers import pipeline |
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classifier = pipeline("image-classification", model="shoni/comic-sans-detector") |
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result = classifier("path/to/image.jpg") |
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print(result) |
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``` |
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## Fine-Tuning Process |
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This model was fine-tuned on a previously fine-tuned font classification model, which itself was based on the ResNet-18 foundation model. The fine-tuning process was conducted using a custom dataset with two classes: `comic` and `not-comic`. |
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## Acknowledgments |
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This project is based on the original font identifier repository by [gaborcselle](https://huggingface.co/gaborcselle/font-identifier). |
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## License |
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Include your preferred license here (e.g., MIT, Apache 2.0, etc.). |
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