import os import streamlit as st import base64 # from transformers import pipeline from PIL import Image from st_clickable_images import clickable_images # pipeline = pipeline(task="image-classification", model="julien-c/hotdog-not-hotdog") st.title("Helmet Detection App: ⛑") confidence=st.slider("Confidence score (0-0.9)", min_value=0.0, max_value=.9, value=.5, step=.1) file_name = st.file_uploader("Upload an image where workers may or may not wear helmets.") if (file_name is not None): col1, col2 = st.columns(2) # img1 ="" # img2 ="" # col1.image(img1, use_column_width=True) # col2.image(img2, use_column_width=True) image = Image.open(file_name) image.save("data/inputImg.jpg") col1.image(image, use_column_width=True) os.system(f"cd yolov5/ && python detect.py --weights ../best.pt --img 416 --conf {confidence} --source ../data/inputImg.jpg") im = Image.open("yolov5/runs/detect/exp/inputImg.jpg") im.save("data/output.jpg") im.close() output =Image.open("data/output.jpg") os.system("rm -rf yolov5/runs") col2.image(output, use_column_width=True) image.close() output.close() elif (st.checkbox('Select an example by clicking on the checkbox.')): image_list=["https://media.istockphoto.com/id/1301722993/photo/group-of-contractors-celebrating-the-end-of-successful-construction-process.jpg?s=612x612&w=0&k=20&c=Xv7sO0AGHITZ6-SdTFrvXYnlWQ_Sc3wAcnGory4n1NA=","https://media.istockphoto.com/id/1472264590/photo/substation-maintenance-engineers.webp?b=1&s=170667a&w=0&k=20&c=dXhPK_sakEhOsAFb6InX4onVoaSgmUZ5A-V6eUlZf8E="] # st.markdown("select a image") clicked = clickable_images( image_list, titles=[f"Image #{str(i)}" for i in range(len(image_list))], div_style={"display": "flex", "justify-content": "space-between", "flex-wrap": "wrap"}, img_style={"margin": "5px", "height": "200px"}, key=None, ) st.markdown(f"Image # {clicked} selected" if clicked > -1 else "No image selected") if clicked>-1: col1, col2 = st.columns(2) file_exp =f"sample/image{clicked+1}.jpg" image = Image.open(file_exp) image.save("data/inputImg.jpg") col1.image(image, use_column_width=True) os.system(f"cd yolov5/ && python detect.py --weights ../best.pt --img 416 --conf {confidence} --source ../data/inputImg.jpg") im = Image.open("yolov5/runs/detect/exp/inputImg.jpg") im.save("data/output.jpg") im.close() output =Image.open("data/output.jpg") col2.image(output, use_column_width=True) image.close() output.close() os.system("rm -rf yolov5/runs")