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import os
from flask import Flask, render_template, request
from transformers import BlipProcessor, BlipForConditionalGeneration
from PIL import Image
# Flask setup
app = Flask(__name__)
UPLOAD_FOLDER = "static/uploads"
os.makedirs(UPLOAD_FOLDER, exist_ok=True)
# Hugging Face BLIP model
processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base")
def generate_caption(image_path):
"""Generate caption from image using BLIP."""
raw_image = Image.open(image_path).convert("RGB")
inputs = processor(raw_image, return_tensors="pt")
out = model.generate(**inputs, max_new_tokens=50)
return processor.decode(out[0], skip_special_tokens=True)
@app.route("/", methods=["GET", "POST"])
@app.route("/Query.html", methods=["GET", "POST"])
def query():
filename = None
caption = None
if request.method == "POST":
file = request.files.get("file-input")
if file and file.filename != "":
filepath = os.path.join(UPLOAD_FOLDER, file.filename)
file.save(filepath)
filename = filepath
# BLIP generates caption
caption = generate_caption(filepath)
return render_template("query.html",
filename=filename,
bot_response=caption)
if __name__ == "__main__":
app.run(host="0.0.0.0", port=7860)
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