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# app.py
import streamlit as st
from transformers import BlipProcessor, BlipForConditionalGeneration
from PIL import Image
import requests
from io import BytesIO
from deep_translator import GoogleTranslator
import torch
# Streamlit page config
st.set_page_config(page_title="AI Image Caption Generator", page_icon="🖼️")
st.title("🖼️ AI Image Caption Generator")
st.write("Upload an image or paste a Google Image URL to get multiple captions generated in your preferred language!")
# Language options
languages = {
"English": "en",
"Urdu": "ur",
"Hindi": "hi",
"French": "fr",
"Spanish": "es",
"Arabic": "ar"
}
# Image input options
upload_option = st.radio("Choose Image Input Method:", ("Upload from Computer", "Paste Image URL"))
uploaded_file = None
image_url = None
if upload_option == "Upload from Computer":
uploaded_file = st.file_uploader("Upload an image", type=["jpg", "png", "jpeg"])
else:
image_url = st.text_input("Paste Image URL (must be direct link ending with .jpg/.png/.jpeg)")
# Language selection
selected_language = st.selectbox("🌐 Choose Output Language", list(languages.keys()))
# Load image based on input
image = None
if uploaded_file:
image = Image.open(uploaded_file).convert('RGB')
elif image_url:
try:
response = requests.get(image_url)
if response.status_code == 200:
image = Image.open(BytesIO(response.content)).convert('RGB')
else:
st.error("Failed to fetch image. Please check the URL.")
except Exception as e:
st.error(f"Error fetching image: {e}")
if image:
st.image(image, caption="Selected Image", width=300)
with st.spinner("Generating captions... please wait ⏳"):
# Resize for model input
resized_image = image.resize((384, 384))
processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
inputs = processor(resized_image, return_tensors="pt")
# Generate multiple captions
out = model.generate(
**inputs,
num_beams=5,
num_return_sequences=3,
max_length=50,
early_stopping=True
)
captions = [processor.decode(o, skip_special_tokens=True) for o in out]
st.success("📝 Captions Generated Successfully!")
st.subheader(f"Here are the captions in {selected_language}:")
for idx, cap in enumerate(captions):
try:
translated_caption = GoogleTranslator(source='auto', target=languages[selected_language]).translate(cap)
except Exception as e:
translated_caption = f"(Translation Error: Showing English) {cap}"
st.text_area(f"✏️ Caption {idx+1}", value=translated_caption, height=80)
st.caption("Tip: You can edit, copy, or download captions easily! ✍️")
else:
st.info("Please upload an image or paste a valid URL to proceed.")
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