Update app.py

app.py

@@ -1,25 +1,30 @@
-from PIL import Image
-from predictions import get_predictions
-import gradio as gr
+import streamlit as st
+from PIL import Image, ImageDraw
+from helper import summarize_predictions_natural_language, render_results_in_image
+from transformers import pipeline
+from tokenizers import Tokenizer, Encoding
+from tokenizers import decoders
+from tokenizers import models
+from tokenizers import normalizers
+from tokenizers import pre_tokenizers
+from tokenizers import processors
+import io
+import matplotlib.pyplot as plt
+import requests
+import inflect
+from predictions import get_predictions  # Replace 'your_module' with the name of the module where your function is defined
 
-def process_image(uploaded_image):
-    return get_predictions(uploaded_image)
+def main():
+    st.title("Object Detection App")
 
-# Define the Gradio Blocks app
-demo = gr.Blocks()
+    uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
 
-# Define components for each step
-with demo:
-    image_input = gr.Image(type="pil", label="Upload Image")
-    processed_image_output = gr.Image(label="Processed Image with Predicted Instances")
-    audio_output = gr.Audio(label="Generated Audio")
-    text_output = gr.Textbox(label="Extracted Text")
+    if uploaded_image is not None:
+        processed_image, text, audio = get_predictions(uploaded_image)
 
-    # Define buttons for each step
-    process_button = gr.Button("Process Image")
+        st.image(processed_image, caption='Processed Image', use_column_width=True)
+        st.write(f"Predictions: {text}")
+        st.audio(audio, format='audio/wav')
 
-    # Define actions for each button
-    process_button.click(process_image, inputs=image_input, outputs=(processed_image_output, audio_output, text_output))
-
-# Launch the Blocks app
-demo.launch()
+if __name__ == '__main__':
+    main()