app.py

import streamlit as st
import cv2
from transformers import pipeline
from PIL import Image
import numpy as np
import time

st.set_page_config(page_title="🎥 TinyLLaVA CCTV Alternative", layout="wide")
st.title("🧠 TinyLLaVA — Webcam Frame-by-Frame (No WebRTC)")

# Load TinyLLaVA pipeline
pipe = pipeline(
    task="image-to-text",
    model="bczhou/tiny-llava-v1-hf",
    trust_remote_code=True,
    device_map="cpu"
)

# OpenCV webcam
cap = cv2.VideoCapture(0)
FRAME_INTERVAL = 30  # process every 30 frames

frame_placeholder = st.empty()
caption_placeholder = st.empty()

frame_count = 0
last_caption = ""

while cap.isOpened():
    ret, frame = cap.read()
    if not ret:
        st.warning("No webcam feed")
        break

    frame = cv2.flip(frame, 1)  # selfie view
    rgb = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB)
    frame_placeholder.image(rgb, channels="RGB", use_column_width=True)

    # every FRAME_INTERVAL frames → run TinyLLaVA
    if frame_count % FRAME_INTERVAL == 0:
        pil_image = Image.fromarray(rgb)
        prompt = "Describe this scene in detail."
        query = f"USER: <image>\n{prompt}\nASSISTANT:"
        result = pipe(query, pil_image)
        last_caption = result[0]["generated_text"]

    caption_placeholder.markdown(f"**Latest:** {last_caption}")

    frame_count += 1

    # Slow down loop to save CPU (adjust if needed)
    time.sleep(0.1)