Create app.py

app.py

@@ -0,0 +1,74 @@
+import streamlit as st
+from transformers import pipeline
+
+classifier = pipeline(task="text-classification", model="SamLowe/roberta-base-go_emotions", top_k=None)
+
+
+st.set_page_config(
+    page_title="Emotion Detection",
+    page_icon=":bar_chart:",
+    layout="centered",  
+)
+
+
+st.markdown(
+    """
+    <style>
+    .stButton > button {
+        background-color: #4CAF50;
+        color: white;
+        font-size: 18px;
+        padding: 10px 20px;
+        border: none;
+        cursor: pointer;
+    }
+    .stButton > button:hover {
+        background-color: #86D8DB;
+    }
+    .stApp {
+        background-color: #73D9C8;  /* Background color */
+    }
+    </style>
+    """,
+    unsafe_allow_html=True,
+)
+
+
+st.title("🎭 Emotion Detection")
+st.markdown("Choose the input type and enter a sentence or upload an image to classify emotions.")
+
+
+input_type = st.radio("Select Input Type", ("Text", "Image"))
+
+
+if input_type == "Text":
+    user_input = st.text_area("Enter a sentence:")
+    uploaded_image = None
+else:
+    uploaded_image = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
+    user_input = ""
+
+
+if st.button("Analyze"):
+    with st.spinner("Analyzing..."):
+        if input_type == "Text" and user_input:
+      
+            model_outputs = classifier(user_input)
+            st.subheader("Emotion Classification Results (Text):")
+        elif input_type == "Image" and uploaded_image is not None:
+            
+            st.image(uploaded_image, use_column_width=True, caption="Uploaded Image")
+            model_outputs = classifier("Analyze this image.")
+            st.subheader("Emotion Classification Results (Image):")
+        else:
+            st.warning("Please enter a sentence or upload an image to analyze.")
+
+        for label_info in model_outputs[0]:
+            label = label_info["label"]
+            score = label_info["score"]
+            st.write(f"- {label}: {score:.4f}")
+
+
+    if st.button("Clear"):
+        user_input = ""
+        uploaded_image = None