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app.py
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import streamlit as st
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from PIL import Image, ImageDraw
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from helper import summarize_predictions_natural_language, render_results_in_image
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from transformers import pipeline
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from tokenizers import Tokenizer, Encoding
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from tokenizers import decoders
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from tokenizers import models
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from tokenizers import normalizers
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from tokenizers import pre_tokenizers
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from tokenizers import processors
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import io
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import matplotlib.pyplot as plt
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import requests
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import inflect
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from predictions import get_predictions # Replace 'your_module' with the name of the module where your function is defined
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def main():
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st.title("Object Detection App")
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uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
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if uploaded_image is not None:
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processed_image, text, audio = get_predictions(uploaded_image)
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st.image(processed_image, caption='Processed Image', use_column_width=True)
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st.write(f"Predictions: {text}")
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st.audio(audio, format='audio/wav')
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if __name__ == '__main__':
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main()
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