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import numpy as np |
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import cv2 |
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import gradio as gr |
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from tensorflow.keras.utils import img_to_array |
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from tensorflow.keras.models import load_model |
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import os |
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model = load_model(r"plant_leaf_diseases_model.h5") |
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classes = ['Pepper_bell_Bacterial_spot', |
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'Pepper_bell_healthy', |
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'Potato_Early_blight', |
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'Potato_Late_blight', |
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'Potato_healthy', |
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'Tomato_Bacterial_spot', |
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'Tomato_Early_blight', |
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'Tomato_Late_blight', |
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'Tomato_Leaf_Mold', |
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'Tomato_Septoria_leaf_spot', |
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'Tomato_Spider_mites_Two_spotted_spider_mite', |
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'Tomato_Target_Spot', |
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'Tomato_Tomato_YellowLeaf_Curl_Virus', |
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'Tomato_Tomato_mosaic_virus', |
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'Tomato_healthy'] |
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def predict_image(img): |
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x = img_to_array(img) |
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x = cv2.resize(x, (256, 256), interpolation=cv2.INTER_AREA) |
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x /= 255 |
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x = np.expand_dims(x, axis=0) |
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image = np.vstack([x]) |
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prediction = model.predict(image)[0] |
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class_probabilities = {class_name: prob for class_name, prob in zip(classes, prediction)} |
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formatted_class_probabilities = {class_name: "{:.2f}".format(prob) for class_name, prob in class_probabilities.items()} |
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return formatted_class_probabilities |
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description_html = """ |
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<p>This model was trained by Moaz Eldsouky. You can find more about me here:</p> |
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<p>GitHub: <a href="https://github.com/MoazEldsouky">GitHub Profile</a></p> |
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<p>LinkedIn: <a href="https://www.linkedin.com/in/moaz-eldesouky-762288251/">LinkedIn Profile</a></p> |
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<p>Kaggle: <a href="https://www.kaggle.com/moazeldsokyx">Kaggle Profile</a></p> |
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<p>This model was trained to classify plant diseases using the Plant Villages dataset.</p> |
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<p>You can see how this model was trained on the following Kaggle Notebook:</p> |
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<p><a href="https://www.kaggle.com/code/moazeldsokyx/plant-leaf-diseases-detection-using-cnn">Kaggle Notebook</a></p> |
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<p>The model achieved an accuracy of <strong>96%</strong> on the test set.</p> |
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<p>Upload a photo to see how the model predicts!</p> |
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""" |
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example_data = [ |
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r"0a0dbf1f-1131-496f-b337-169ec6693e6f___NREC_B.Spot 9241.JPG", |
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r"0e69c47d-72c6-4fc6-9437-910c95b183dc___JR_HL 8113.JPG", |
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r"0c4f6f72-c7a2-42e1-9671-41ab3bf37fe7___RS_Early.B 6752.JPG", |
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r"1f9870b3-899e-46fb-98c9-cfc2ce92895b___RS_HL 1816.JPG", |
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r"3f0fd699-1ce7-437e-a899-662a51d59974___RS_LB 2904.JPG", |
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r"01b2013e-4030-4cd0-843c-2dbacf5f3758___Com.G_TgS_FL 8398.JPG", |
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r"0ce66ec5-0bb7-4fde-9c61-750a1a150f75___UF.GRC_YLCV_Lab 02219.JPG", |
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r"0afe3bbd-b18b-4c70-8fbd-072844e742a2___GCREC_Bact.Sp 3434.JPG", |
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r"0ba3d536-8732-4ea1-b3e1-a1be86e5dc6a___RS_Erly.B 9499.JPG", |
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r"2e96661f-a313-4deb-bf32-1eacbc10c48d___GH_HL Leaf 424.JPG" |
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] |
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gr.Interface( |
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fn=predict_image, |
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inputs="image", |
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outputs=gr.Label(num_top_classes=15,min_width=360), |
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title="Plant Diseases Classification 🌱🦠", |
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description=description_html, |
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allow_flagging='never', |
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examples=example_data |
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).launch() |
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