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app.py

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+import zipfile
+import os
+import gradio as gr
+import numpy as np
+from keras.models import load_model
+from PIL import Image
+from keras.utils import img_to_array
+from keras.applications.resnet import preprocess_input
+
+
+
+zip_path = 'resnet101_model.zip'
+
+extract_dir = 'resnet101_model'
+
+
+if not os.path.isdir(extract_dir):
+
+    with zipfile.ZipFile(zip_path, 'r') as zip_ref:
+
+        zip_ref.extractall(extract_dir)
+
+
+model = load_model(os.path.join(extract_dir, 'resnet101_model'))
+
+
+class_names = ['cloudy', 'desert', 'green_area', 'water']
+
+
+def predict_image(file_path):
+
+    with open(file_path, "rb") as f:
+
+        imageUploadedByUser = Image.open(f)
+
+        imageUploadedByUser = imageUploadedByUser.resize((224, 224))
+
+        if imageUploadedByUser.mode != 'RGB':
+            imageUploadedByUser = imageUploadedByUser.convert('RGB')
+
+        image_to_arr = img_to_array(imageUploadedByUser)
+
+        image_to_arr_preprocess_input = preprocess_input(image_to_arr)
+
+        image_to_arr_preprocess_input_expand_dims = np.expand_dims(
+            image_to_arr_preprocess_input, axis=0)
+
+        prediction = model.predict(
+            image_to_arr_preprocess_input_expand_dims)[0]
+
+        prediction_argmax = np.argmax(prediction)
+
+        prediction_final_result = class_names[prediction_argmax]
+
+        return f'The predicted satellite image is {prediction_final_result}.'
+
+
+custom_css = """
+    .desc { text-align: center; }
+"""
+
+
+interfaceOfGradio = gr.Interface(
+    fn=predict_image,
+    inputs=gr.File(type="filepath",
+                   label="Upload Satellite Image", file_count="single"),
+    outputs="text",
+    description="<p class='desc'>" +
+    "Upload a satellite image on the left and see the prediction result on the right." + "</p>",
+    css=custom_css
+)
+
+
+interfaceOfGradio.launch()

requirements.txt

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+numpy==1.26.4
+tensorflow==2.10.0
+gradio==4.23.0
+keras==2.10.0

resnet101_model.zip

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+version https://git-lfs.github.com/spec/v1
+oid sha256:a03c57bfcd1c949010bd2da9bdc6536d0c94784cbc2b2c4873bbc8ddad3e5c16
+size 303606453