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| # Python In-built packages | |
| from pathlib import Path | |
| import PIL | |
| import time | |
| # External packages | |
| import streamlit as st | |
| import cv2 | |
| # Local Modules | |
| import settings | |
| import helper | |
| # Setting page layout | |
| st.set_page_config( | |
| page_title="Object Detection using YOLOv9", | |
| page_icon="🤖", | |
| layout="wide", | |
| initial_sidebar_state="expanded" | |
| ) | |
| # Main page heading | |
| st.title("Object Detection using YOLOv9") | |
| # Sidebar | |
| st.sidebar.header("ML Model Config") | |
| # Model Options | |
| model_type = st.sidebar.radio( | |
| "Select Task", ['Detection', 'Segmentation']) | |
| confidence = float(st.sidebar.slider( | |
| "Select Model Confidence", 25, 100, 40)) / 100 | |
| # Selecting Detection Or Segmentation | |
| if model_type == 'Detection': | |
| model_path = Path(settings.DETECTION_MODEL) | |
| elif model_type == 'Segmentation': | |
| model_path = Path(settings.SEGMENTATION_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("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'): | |
| 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.VIDEO: | |
| helper.play_stored_video(confidence, model) | |
| elif source_radio == settings.YOUTUBE: | |
| helper.play_youtube_video(confidence, model) | |
| elif source_radio == settings.WEBCAM: # Adding webcam option | |
| st.sidebar.markdown("**Webcam**") | |
| webcam = cv2.VideoCapture(1) | |
| if not webcam.isOpened(): | |
| st.error("Unable to open webcam. Please make sure it's connected.") | |
| else: | |
| webcam_status = st.sidebar.empty() | |
| start_stop_button = st.sidebar.button("Start Webcam") | |
| if start_stop_button: | |
| webcam_started = True | |
| webcam_status.text("Webcam Started!") | |
| while webcam_started: | |
| ret, frame = webcam.read() | |
| if not ret: | |
| st.error("Failed to capture frame from webcam") | |
| break | |
| frame = cv2.cvtColor(frame, cv2.COLOR_BGR2RGB) | |
| # Perform object detection on the frame | |
| res = model.predict(frame, conf=confidence) | |
| boxes = res[0].boxes | |
| frame = res[0].plot()[:, :, ::-1] | |
| # Display the frame | |
| st.image(frame, channels="RGB", use_column_width=True) | |
| stop_button = st.sidebar.button("Stop Webcam" + str(hash(time.time()))) # Unique key | |
| if stop_button: | |
| webcam_started = False | |
| webcam_status.text("Webcam Stopped!") | |
| webcam.release() | |