created text_image file

text_to_image.py

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+import streamlit as st
+# pipelines will help to load the model from huggingface
+from transformers import pipeline
+# load_dotenv(find_dotenv())
+st.title("Image to text generation App 🕵️‍♂️")  
+
+uploaded_file = st.file_uploader("Choose a file..",type= ['png', 'jpg'])
+if uploaded_file is not None:
+    up_image=uploaded_file.name
+    #st.image(up_image)
+    st.image(up_image,caption="Uploaded Image",use_column_width=True)
+    image_to_text=pipeline("image-to-text", model="Salesforce/blip-image-captioning-large")
+    text=image_to_text(up_image)[0]["generated_text"]
+    st.subheader(text)
+    # #return text