app.py

import streamlit as st
from PIL import Image
from ultralytics import YOLO
import numpy as np
import cv2

# --- Load YOLOv8 Model ---
model = YOLO('yolov8n.pt')  # Nano model, fast and small

# --- Streamlit UI ---
st.title("📸 Object Counter App (YOLOv8)")

uploaded_file = st.file_uploader("Upload an Image", type=['jpg', 'jpeg', 'png'])

if uploaded_file is not None:
    image = Image.open(uploaded_file).convert('RGB')
    st.image(image, caption="Uploaded Image", use_column_width=True)

    st.write("🔎 Detecting objects...")

    # Convert PIL image to NumPy array
    img_array = np.array(image)

    # Inference
    results = model.predict(img_array)

    # Get number of detected objects
    num_objects = len(results[0].boxes)

    st.success(f"✅ Total objects detected: {num_objects}")

    # List detected object classes
    class_names = [model.names[int(cls)] for cls in results[0].boxes.cls]
    st.write(f"Detected Items: {class_names}")

    # Draw boxes on image
    result_img = results[0].plot()

    st.image(result_img, caption='Detected Objects', use_column_width=True)

st.write("Meraj Graphics ❤️ ")