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Update app.py
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app.py
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@@ -1,21 +1,21 @@
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import streamlit as st
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import transformers
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from transformers import pipeline
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import PIL
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from PIL import Image
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import requests
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from transformers import AutoProcessor, AutoModelForZeroShotImageClassification
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pipe = pipeline("summarization", model="google/pegasus-xsum")
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agepipe = pipeline("image-classification", model="dima806/facial_age_image_detection")
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imgpipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32")
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emopipe = pipeline("text-classification", model="michellejieli/emotion_text_classifier")
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st.title("NLP APP")
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option = st.sidebar.selectbox(
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"Choose a task",
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("Summarization", "Age Detection", "Emotion Detection", "Image Classification")
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)
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if option == "Summarization":
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st.title("Text Summarization")
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text = st.text_area("Enter text to summarize")
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@@ -26,16 +26,12 @@ if option == "Summarization":
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st.write("Please enter text to summarize.")
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elif option == "Age Detection":
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st.title("Welcome to age detection")
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uploaded_files = st.file_uploader("Choose a image file",type="jpg")
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if uploaded_files is not None:
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st.write("Detected age is ",agepipe(Image)[0]["label"])
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elif option == "Image Classification":
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st.title("Welcome to object detection")
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uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "jpeg", "png"])
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text = st.text_area("Enter possible class names (comma-separated)")
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if st.button("Submit"):
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@@ -50,26 +46,34 @@ elif option == "Image Classification":
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st.write("Please upload an image file and enter class names.")
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elif option == "Emotion Detection":
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st.title("Detect your emotion")
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text=st.text_area("Enter your text")
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if st.button("Submit"):
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if text:
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emotion=emopipe(text)[0]["label"]
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if emotion == "sadness":
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elif emotion == "joy":
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elif emotion == "fear":
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elif emotion == "anger":
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elif emotion == "neutral":
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elif emotion == "disgust":
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elif emotion == "surprise":
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else:
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st.write("Please enter text.")
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else:
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st.title("None")
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import streamlit as st
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from transformers import pipeline
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from PIL import Image
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import requests
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# Define pipelines
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pipe = pipeline("summarization", model="google/pegasus-xsum")
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agepipe = pipeline("image-classification", model="dima806/facial_age_image_detection")
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imgpipe = pipeline("zero-shot-image-classification", model="openai/clip-vit-base-patch32")
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emopipe = pipeline("text-classification", model="michellejieli/emotion_text_classifier")
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transpipe = pipeline("translation_en_to_fr")
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st.title("NLP APP")
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option = st.sidebar.selectbox(
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"Choose a task",
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("Summarization", "Age Detection", "Emotion Detection", "Image Classification", "Translation")
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)
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if option == "Summarization":
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st.title("Text Summarization")
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text = st.text_area("Enter text to summarize")
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st.write("Please enter text to summarize.")
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elif option == "Age Detection":
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st.title("Welcome to age detection")
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uploaded_files = st.file_uploader("Choose an image file", type="jpg")
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if uploaded_files is not None:
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image = Image.open(uploaded_files)
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st.write("Detected age is ", agepipe(image)[0]["label"])
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elif option == "Image Classification":
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st.title("Welcome to object detection")
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uploaded_file = st.file_uploader("Choose an image file", type=["jpg", "jpeg", "png"])
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text = st.text_area("Enter possible class names (comma-separated)")
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if st.button("Submit"):
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st.write("Please upload an image file and enter class names.")
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elif option == "Emotion Detection":
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st.title("Detect your emotion")
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text = st.text_area("Enter your text")
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if st.button("Submit"):
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if text:
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emotion = emopipe(text)[0]["label"]
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if emotion == "sadness":
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st.write("Emotion : ", emotion, "π’")
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elif emotion == "joy":
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st.write("Emotion : ", emotion, "π")
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elif emotion == "fear":
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st.write("Emotion : ", emotion, "π¨")
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elif emotion == "anger":
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st.write("Emotion : ", emotion, "π‘")
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elif emotion == "neutral":
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st.write("Emotion : ", emotion, "π")
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elif emotion == "disgust":
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st.write("Emotion : ", emotion, "π€’")
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elif emotion == "surprise":
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st.write("Emotion : ", emotion, "π²")
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else:
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st.write("Please enter text.")
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elif option == "Translation":
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st.title("Text Translation")
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text = st.text_area("Enter text to translate from English to French")
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if st.button("Translate"):
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if text:
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translation = transpipe(text)[0]["translation_text"]
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st.write("Translation:", translation)
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else:
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st.write("Please enter text to translate.")
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else:
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st.title("None")
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