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--- |
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language: en |
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tags: |
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- tensorflow |
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- classification |
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- plant-disease-detection |
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license: mit |
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--- |
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# Leafy Vegetable Disease Detection Model |
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## Model Description |
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This model is trained to detect diseases in leafy vegetables using images. It utilizes the PlantVillage dataset to identify various plant diseases. |
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## Intended Use |
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This model can be used for: |
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- Detecting diseases in images of leafy vegetables. |
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- Providing feedback and recommendations for farmers and agricultural specialists. |
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## How to Use |
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You can use this model by sending an image of a leafy vegetable to the Inference API endpoint. |
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## Model Details |
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- **Input**: Image (JPEG/PNG) |
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- **Output**: Prediction of disease type with confidence scores. |
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## Training Data |
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This model is trained on the PlantVillage dataset, which contains labeled images of healthy and diseased plants. |
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## Limitations |
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- The model's performance may vary based on image quality and environmental conditions. |
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- It may not recognize diseases not present in the training dataset. |
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## Example |
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Here’s an example of how to use this model with the Inference API: |
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```python |
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import requests |
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url = "https://api-inference.huggingface.co/models/JayGab/Leafy-Vegetable-Disease-Detection" |
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files = {'file': open('path_to_image.jpg', 'rb')} |
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response = requests.post(url, files=files) |
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print(response.json()) |
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