Delete app.py

app.py

@@ -1,87 +0,0 @@
-import streamlit as st
-from PIL import Image
-import requests
-
-# Dummy functions to simulate the behavior of the removed pipelines
-def summarize(text):
-    return "This is a summary of the text."
-
-def detect_age(image):
-    return "Age: 25-30"
-
-def classify_image(image, candidate_labels):
-    return [{"label": label, "score": 0.5} for label in candidate_labels]
-
-def detect_emotion(text):
-    return "joy"
-
-def translate(text):
-    return "Ceci est une traduction."
-
-st.title("NLP APP")
-option = st.sidebar.selectbox(
-    "Choose a task",
-    ("Summarization", "Age Detection", "Emotion Detection", "Image Classification", "Translation")
-)
-
-if option == "Summarization":
-    st.title("Text Summarization")
-    text = st.text_area("Enter text to summarize")
-    if st.button("Summarize"):
-        if text:
-            st.write("Summary:", summarize(text))
-        else:
-            st.write("Please enter text to summarize.")
-elif option == "Age Detection":
-    st.title("Welcome to age detection")
-    uploaded_files = st.file_uploader("Choose an image file", type="jpg")
-    if uploaded_files is not None:
-        image = Image.open(uploaded_files)
-        st.write(detect_age(image))
-elif option == "Image Classification":
-    st.title("Welcome to object detection")
-    uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "jpeg", "png"])
-    text = st.text_area("Enter possible class names (comma-separated)")
-    if st.button("Submit"):
-        if uploaded_file is not None and text:
-            candidate_labels = [t.strip() for t in text.split(',')]
-            image = Image.open(uploaded_file)
-            st.image(image, caption="Uploaded Image", use_column_width=True)
-            classification_result = classify_image(image, candidate_labels)
-            for result in classification_result:
-                st.write(f"Label: {result['label']}, Score: {result['score']}")
-        else:
-            st.write("Please upload an image file and enter class names.")
-elif option == "Emotion Detection":
-    st.title("Detect your emotion")
-    text = st.text_area("Enter your text")
-    if st.button("Submit"):
-        if text:
-            emotion = detect_emotion(text)
-            if emotion == "sadness":
-                st.write("Emotion : ", emotion, "😢")
-            elif emotion == "joy":
-                st.write("Emotion : ", emotion, "😃")
-            elif emotion == "fear":
-                st.write("Emotion : ", emotion, "😨")
-            elif emotion == "anger":
-                st.write("Emotion : ", emotion, "😡")
-            elif emotion == "neutral":
-                st.write("Emotion : ", emotion, "😐")
-            elif emotion == "disgust":
-                st.write("Emotion : ", emotion, "🤢")
-            elif emotion == "surprise":
-                st.write("Emotion : ", emotion, "😲")
-        else:
-            st.write("Please enter text.")
-elif option == "Translation":
-    st.title("Text Translation")
-    text = st.text_area("Enter text to translate from English to French")
-    if st.button("Translate"):
-        if text:
-            translation = translate(text)
-            st.write("Translation:", translation)
-        else:
-            st.write("Please enter text to translate.")
-else:
-    st.title("None")