{"id":22636531,"url":"https://github.com/mrdvince/anga","last_synced_at":"2026-04-18T04:02:17.100Z","repository":{"id":52282505,"uuid":"200441075","full_name":"mrdvince/anga","owner":"mrdvince","description":"Using a pre-trained efficientnet (for experimental purposes) to classifier plant diseases given an image. 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Create (and activate) a new environment with Python 3.6.\n\t- __Linux__ or __Mac__: \n\t```bash\n\tconda create --name py39 python=3.9.2\n\tconda activate py39\n\t```\nalternatively, use virtual environments if you don't have Anaconda installed.\n\n2. Clone the repository (if you haven't already!), and navigate to the `anga` folder.  Then, install several dependencies.\n```bash\ngit clone https://github.com/mrdvince/anga\ncd anga\n```\n\n## FastAPI endpoint\n\nA minimal API endpoint to expose your model, you can make it more robust if you want.\n\nRun ```uvicorn api.main:app``` and visit you ```local ip``` if running locally port ```8000``` playground to access the interactive docs (included by default). i.e. `http://127.0.0.1:8000/playground`\n\n![png](screenshots/fastapi.png)\n\n\n## Training\nSee the README on this [link](https://github.com/mrdvince/pytorchtemplate) has been([forked from](https://github.com/victoresque/pytorch-template)). The readme contains information on the folder structures and how to modify the hyperparameters to your liking.\n\nOn a high level:\n- the config json file contains the model hyperparamaters and other settings\n\nRun `python train.py -c config.json` to train the model.\n\n## Metrics\nLogged using tensorboard\n### Train and Validation Accuracies \n![png](screenshots/acc.png)\n\n### Train and Validation Loss \n![png](screenshots/loss.png)\n\n\n## Inputs\n![png](screenshots/input.png)\n","project_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmrdvince%2Fanga","html_url":"https://awesome.ecosyste.ms/projects/github.com%2Fmrdvince%2Fanga","lists_url":"https://awesome.ecosyste.ms/api/v1/projects/github.com%2Fmrdvince%2Fanga/lists"}