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  1. app.py +23 -0
  2. model.pkl +3 -0
  3. requirements.txt +5 -0
  4. test_image1.jpg +0 -0
  5. test_image2.jpg +0 -0
app.py ADDED
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+ from fastai.vision.all import * # Importing the necessary fastai modules
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+ import gradio as gr # Importing Gradio for creating the web interface
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+ import timm # Importing timm for model management
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+
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+ # Load the pre-trained model
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+ learn = load_learner('model.pkl')
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+
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+ # Extract categories (class labels) from the DataLoader
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+ categories = learn.dls.vocab
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+
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+ # Function to classify an image
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+ def classify_image(img):
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+ _, _, probs = learn.predict(img)
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+ return dict(zip(categories, map(float, probs))) # Map categories to their probabilities
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+
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+ # Define Gradio input and output components
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+ image = gr.Image() # Image input
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+ label = gr.Label() # Output label to display classification
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+ examples = ['test_image1.jpg', 'test_image2.jpg'] # Example images for demonstration
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+
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+ # Create and launch the Gradio interface
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+ intf = gr.Interface(fn=classify_image, inputs=image, outputs=label, examples=examples)
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+ intf.launch()
model.pkl ADDED
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+ version https://git-lfs.github.com/spec/v1
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+ oid sha256:72b878320ef7decea7c866e92fd6616e77ece3eb865a3166d7fbb1fddfe076bf
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+ size 114611602
requirements.txt ADDED
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+ fastai==2.7.12
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+ gradio==3.34.0
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+ timm==0.9.2
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+ torch==2.0.1
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+ torchvision==0.15.2
test_image1.jpg ADDED
test_image2.jpg ADDED