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import streamlit as st
import cv2
import numpy as np
import PIL
from pathlib import Path
# Local Modules
import settings
import helper
from helper import _display_detected_frames # Ensure this import
# Setting page layout
st.set_page_config(
page_title="Object Detection using YOLO",
page_icon="🤖",
layout="wide",
initial_sidebar_state="expanded"
)
# Main page heading
st.title("Object Detection using YOLOv10 - CPU Only")
# Sidebar
st.sidebar.header("ML Model Config")
# Model Options
confidence = float(st.sidebar.slider("Select Model Confidence", 25, 100, 40)) / 100
# Load Pre-trained ML Model
model_path = Path(settings.DETECTION_MODEL)
try:
model = helper.load_model(model_path)
except Exception as ex:
st.error(f"Unable to load model. Check the specified path: {model_path}")
st.error(ex)
st.sidebar.header("Image/Video Config")
source_radio = st.sidebar.radio("Select Source", settings.SOURCES_LIST)
source_img = None
# If image is selected
if source_radio == settings.IMAGE:
source_img = st.sidebar.file_uploader("Choose an image...", type=("jpg", "jpeg", "png", 'bmp', 'webp'))
col1, col2 = st.columns(2)
with col1:
try:
if source_img is None:
default_image_path = str(settings.DEFAULT_IMAGE)
default_image = PIL.Image.open(default_image_path)
st.image(default_image_path, caption="Default Image", use_column_width=True)
else:
uploaded_image = PIL.Image.open(source_img)
st.image(source_img, caption="Uploaded Image", use_column_width=True)
except Exception as ex:
st.error("Error occurred while opening the image.")
st.error(ex)
with col2:
if source_img is None:
default_detected_image_path = str(settings.DEFAULT_DETECT_IMAGE)
default_detected_image = PIL.Image.open(default_detected_image_path)
st.image(default_detected_image_path, caption='Detected Image', use_column_width=True)
else:
if st.sidebar.button('Detect Objects'):
try:
# Convert PIL image to OpenCV format
image_np = np.array(uploaded_image)
_display_detected_frames(confidence, model, st, image_np)
except Exception as ex:
st.error("Error occurred while detecting objects.")
st.error(ex)
# If video is selected
elif source_radio == settings.VIDEO:
helper.play_stored_video(confidence, model)
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