Upload app (3).py

app (3).py

@@ -1,36 +1,33 @@
 import streamlit as st
 from PIL import Image
-from io import StringIO
 import pandas as pd
 from transformers import pipeline
 
-# Create an object detection pipeline
-classifier = pipeline("object-detection", model="chayanee/Detected_img")
+# Create a sentiment analysis pipeline
+sentiment_analysis = pipeline("sentiment-analysis", model="chayanee/Detected_img")
 
-def main():
-    st.title("Object Detection on Images")
+# Set the title for your Streamlit app
+st.title("NLP and Image Analysis")
 
-    # File Upload Widget
-    uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "png", "jpeg"])
+# Text Input Widget
+text_input = st.text_area("Enter some text for sentiment analysis:")
 
-    if uploaded_file is not None:
-        # Display the uploaded image
-        st.image(uploaded_file, caption="Uploaded Image", use_column_width=True)
-
-        # Perform object detection
-        image = Image.open(uploaded_file)
-        results = classifier(image)
+# Image Upload Widget
+uploaded_image = st.file_uploader("Upload an image for analysis", type=["jpg", "jpeg", "png"])
 
-        # Display object detection results
-        st.subheader("Object Detection Results")
-        for result in results:
-            label = result["label"]
-            score = result["score"]
-            box = result["box"]
-            st.write(f"Label: {label}, Score: {score:.2f}")
-            st.image(image.crop(box), caption=f"Object: {label}", use_column_width=True)
+# Perform sentiment analysis when the user clicks a button
+if st.button("Analyze"):
+    # Perform sentiment analysis on the text
+    if text_input:
+        sentiment_result = sentiment_analysis(text_input)
+        st.write("Sentiment Analysis Result:")
+        st.write(sentiment_result)
 
-    st.button("Click to Detect Objects", type="primary")
+    # Analyze the uploaded image if available
+    if uploaded_image:
+        # Display the uploaded image
+        image = Image.open(uploaded_image)
+        st.image(image, caption="Uploaded Image", use_column_width=True)
 
 if __name__ == "__main__":
     main()