Update app.py

app.py

@@ -1,27 +1,32 @@
-import gradio as gr
+import streamlit as st
+from PIL import Image
+from PIL import Image, ImageDraw
+from image_whisper_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 PIL import Image
+from predictions import get_predictions  # Replace 'your_module' with the name of the module where your function is defined
 
-# Load the image-to-text pipeline
-image_to_text_pipelines = {
-    "Salesforce/blip-image-captioning-base": pipeline("image-to-text", model="Salesforce/blip-image-captioning-base"),
-    # Add more models if needed
-}
+def main():
+    st.title("Object Detection App")
 
-def generate_caption(input_image, model_name="Salesforce/blip-image-captioning-base"):
-    # Generate caption for the input image using the selected model
-    image_to_text_pipeline = image_to_text_pipelines[model_name]
-    caption = image_to_text_pipeline(input_image)[0]['generated_text']
-    return caption
+    uploaded_image = st.file_uploader("Upload an image", type=["jpg", "jpeg", "png"])
 
-# Interface for launching the model
-interface = gr.Interface(
-    fn=generate_caption,
-    inputs=gr.Image(type='pil', label="Input Image"),
-    outputs="text",
-    title="Image Captioning Model",
-    description="This model generates captions for images.",
-    theme="default",
-)
+    if uploaded_image is not None:
+        processed_image, text, audio = get_predictions(uploaded_image)
 
-# Launch the interface
-interface.launch()
+        st.image(processed_image, caption='Processed Image', use_column_width=True)
+        st.write(f"Predictions: {text}")
+        st.audio(audio, format='audio/wav')
+
+if __name__ == '__main__':
+    main()