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app.py

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+from fastai.vision.all import *  # Importing the necessary fastai modules
+import gradio as gr  # Importing Gradio for creating the web interface
+import timm  # Importing timm for model management
+
+# Load the pre-trained model
+learn = load_learner('model.pkl')
+
+# Extract categories (class labels) from the DataLoader
+categories = learn.dls.vocab
+
+# Function to classify an image
+def classify_image(img):
+    _, _, probs = learn.predict(img)
+    return dict(zip(categories, map(float, probs)))  # Map categories to their probabilities
+
+# Define Gradio input and output components 
+image = gr.Image(width=224, height=224)  # Image input
+label = gr.Label()  # Output label to display classification
+examples = ['test_image1.jpg', 'test_image2.jpg']  # Example images for demonstration
+
+# Create and launch the Gradio interface
+intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
+intf.launch()

model.pkl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b1dc6a8b22855e77b9e7a27d5efcd702682cc3cd368eaa852e2b5047104cbe39
+size 46976690

requirements.txt

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+numpy==1.26.4
+scipy==1.11.4
+scikit-learn==1.3.2
+fastai==2.7.17
+gradio==4.44.1
+timm==1.0.9
+torch==2.2.1
+torchvision==0.17.1
+setuptools