app.py

# Python In-built packages
from pathlib import Path

import PIL
# External packages
import streamlit as st

import algorithm
import helper
# Local Modules
import settings

st.set_page_config(
    page_title="YOLOv8 目标检测",
    page_icon="🤖",
    layout="wide",
    initial_sidebar_state="expanded"  # 或者 "collapsed"
)



# # Main page heading
st.title("目标检测预览")

# Sidebar
st.sidebar.header("模型配置")

# Model Options
model_type = st.sidebar.selectbox(
    "任务选择", ['检测', '分割',"周界入侵","安防检测"])

confidence = float(st.sidebar.slider(
    "选择模型Confidence", 25, 100, 40)) / 100

# Selecting Detection Or Segmentation
if model_type == '检测':
    model_path = Path(settings.DETECTION_MODEL)
elif model_type == '分割':
    model_path = Path(settings.SEGMENTATION_MODEL)
elif model_type == "周界入侵":
    model_path = Path(settings.DETECTION_MODEL)
elif model_type == "安防检测":
    model_path = Path(settings.SECURITY_MODEL)

# Load Pre-trained ML 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("图像/视频 配置")
source_radio = st.sidebar.radio(
    "选择来源", settings.SOURCES_LIST)

source_img = None
# If image is selected
if source_radio == settings.IMAGE:
    source_img = st.sidebar.file_uploader(
        "选择一张图像...", 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="默认图像",
                         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='检测图像',
                     use_column_width=True)
        else:
            if st.sidebar.button('检测目标'):
                res = model.predict(uploaded_image,
                                    conf=confidence
                                    )
                boxes = res[0].boxes
                res_plotted = res[0].plot()[:, :, ::-1]
                st.image(res_plotted, caption='Detected Image',
                         use_column_width=True)
                try:
                    with st.expander("Detection Results"):
                        for box in boxes:
                            st.write(box.data)
                except Exception as ex:
                    # st.write(ex)
                    st.write("No image is uploaded yet!")



elif source_radio == settings.RTSP:
    if model_type == '检测':

        algorithm.YoloV8Detection().play_rtsp_stream(confidence,model)

    elif model_type == '分割':

        algorithm.YoloV8Detection().play_rtsp_stream(confidence,model)

    elif model_type == "周界入侵":

        algorithm.BoundaryDetection().play_rtsp_stream(confidence,model)

    elif model_type == "安防检测":

        algorithm.YoloV8Detection().play_rtsp_stream(confidence,model)
    #helper.play_rtsp_stream(confidence, model)

else:
    st.error("Please select a valid source type!")