NoorIlyas commited on
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fc9bb15
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1 Parent(s): e6b400a

Create app.py

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  1. app.py +49 -0
app.py ADDED
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+ import streamlit as st
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+ import torch
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+ from torchvision import models, transforms
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+ from PIL import Image
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+
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+ # Load a pre-trained ResNet model
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+ model = models.resnet50(pretrained=True)
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+ model.eval()
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+
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+ # Define the transformations for the input image
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+ transform = transforms.Compose([
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+ transforms.Resize((224, 224)),
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+ transforms.ToTensor(),
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+ transforms.Normalize(mean=[0.485, 0.456, 0.406], std=[0.229, 0.224, 0.225]),
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+ ])
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+
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+ def classify_image(image):
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+ # Preprocess the input image
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+ image = transform(image)
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+ image = image.unsqueeze(0) # Add batch dimension
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+
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+ # Make a prediction
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+ with torch.no_grad():
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+ output = model(image)
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+
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+ # Get the predicted class
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+ _, predicted_class = torch.max(output, 1)
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+
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+ return predicted_class.item()
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+
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+ def main():
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+ st.title("Image Classification with PyTorch and Streamlit")
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+
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+ uploaded_file = st.file_uploader("Choose a file", type=["jpg", "jpeg", "png"])
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+
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+ if uploaded_file is not None:
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+ # Display the uploaded image
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+ image = Image.open(uploaded_file)
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+ st.image(image, caption="Uploaded Image.", use_column_width=True)
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+
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+ # Make a prediction
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+ class_idx = classify_image(image)
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+
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+ # Display the result
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+ class_label = str(class_idx)
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+ st.write("Class Prediction: ", class_label)
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+
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+ if __name__ == "__main__":
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+ main()