init

Requirements.txt

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+

app.py

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+
+
+import gradio as gr
+from datasets import load_dataset
+from PIL import Image
+import matplotlib.pyplot as plt
+import numpy as np
+import tensorflow as tf
+from tensorflow.keras import layers
+from tensorflow.keras.models import Sequential
+from tensorflow.keras.models import load_model
+from keras.preprocessing import image
+
+model3 = load_model('best_beans.h5')
+
+leaf_class=['angular_leaf_spot', 'bean_rust', 'healthy']
+
+def classify_image(img):
+  img_width, img_height = 224, 224
+  img = image.load_img(img, target_size = (img_width, img_height))
+  img = image.img_to_array(img)
+  img = np.expand_dims(img, axis = 0)
+  prediction = model3.predict(img)[0]
+  return {leaf_class[i]: float(prediction[i]) for i in range(3)}
+
+gr.Interface(fn=classify_image,
+             inputs=gr.Image( type ="filepath"),
+             outputs=gr.Label(num_top_classes=1)).launch(debug=True)