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| title: Pytorch Resnet34 Bird Classification | |
| emoji: 👀 | |
| colorFrom: yellow | |
| colorTo: gray | |
| sdk: gradio | |
| sdk_version: 3.16.1 | |
| app_file: app.py | |
| pinned: false | |
| license: gpl-3.0 | |
| # Pytorch Resnet34 Bird Classification | |
| The project is an implementation of the ResNet34 model as per the [Microsoft Research Paper](https://arxiv.org/abs/1512.03385). The model is build using PyTorch and is trained on the [Birds Classification Dataset](https://www.kaggle.com/datasets/gpiosenka/100-bird-species) from Kaggle. | |
| ## 🚀 Getting Started | |
| All the code for training the model and exporting to ONNX format is present in the [notebook](notebooks) folder or you can use this [Kaggle Notebook](https://www.kaggle.com/gauthamkrishnan119/pytorch-resnet34-birds-classification) for training the model. It took ~1.5 hours to train the model on the complete dataset using a P100 GPU. The [app.py](app.py) file contains the code for deploying the model using Gradio. | |
| ## 🤗 Demo | |
| You can try out the model on [Hugging Face Spaces](https://huggingface.co/spaces/gauthamk/pytorch-resnet34-bird-classification) | |
| ## 🖥️ Sample Interface | |
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