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README.md

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----
-title: WasteDetection
-emoji: 🌖
-colorFrom: yellow
-colorTo: red
-sdk: streamlit
-sdk_version: 1.35.0
-app_file: app.py
-pinned: false
-license: cc
----
-
-Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference
+---
+title: WasteDetection
+emoji: 🌖
+colorFrom: yellow
+colorTo: red
+sdk: streamlit
+sdk_version: 1.35.0
+app_file: app.py
+pinned: false
+license: cc
+---
+
+Check out the configuration reference at https://huggingface.co/docs/hub/spaces-config-reference

app.py

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+import streamlit as st
+from PIL import Image
+import numpy as np
+
+from ultralytics import YOLO
+from io import BytesIO
+# Initialize session state
+
+if "page" not in st.session_state:
+    st.session_state.page = "Home"
+
+# Load the YOLO model with pre-trained weights
+model_path = r"runs\classify\train4\weights\best.pt"  # Use raw string
+model = YOLO(model_path)
+
+# Define the function to make predictions
+def make_predictions(image_data):
+    image = Image.open(BytesIO(image_data))
+    results = model(image)
+    names_dict = results[0].names
+    probs = results[0].probs.data.tolist()
+    predicted_item_class = names_dict[np.argmax(probs)].split('_')[0]
+    predicted_category = names_dict[np.argmax(probs)].split('_')[1]
+    return image, predicted_item_class, predicted_category
+
+# Define the function to capture photo and perform waste classification
+def take_photo_and_classify():
+    picture = st.camera_input("Take a picture")
+
+    if picture:
+        # Make prediction
+        image, predicted_item_class, predicted_category = make_predictions(picture.getvalue())
+
+        # Display the captured image and prediction
+        st.image(image, caption='Captured Image')
+        st.write('Predicted Waste Item Class:', predicted_item_class)
+        st.write('Predicted Waste Category:', predicted_category)
+    else:
+        st.warning("No image captured.")
+
+# Define the footer content
+def sidebar_footer():
+    st.sidebar.markdown("---")
+    st.sidebar.markdown("<div style='text-align: center; font-size: 12px; font-family: Times New Roman; margin-bottom: 5px;'>Medical waste detection and classification</div>", unsafe_allow_html=True)
+    st.sidebar.markdown("<div style='text-align: center; font-size: 12px; font-family: Times New Roman;'>Omkar Bhalerao | Srushti Bobe | Priyanka Adhav</div>", unsafe_allow_html=True)
+
+st.sidebar.image(r"side-unscreen (1).gif", use_column_width=True)
+
+# Center-align sidebar content and add space after the line
+st.sidebar.markdown("<div style='text-align: center; margin-bottom: 30px;'>"
+                    "<b>Exploring pathways to innovation and knowledge.</b>"
+                    "</div>", unsafe_allow_html=True)
+
+nav_options = ["🏠 Home", "📝 Problem" , "🔧 Working", "📊 Classification", "👩‍💻 About"]
+icons = ["➜", "➜", "➜", "➜", "➜"]
+for option, icon in zip(nav_options, icons):
+    if st.sidebar.button(f"{icon} {option}", key=option):
+        st.session_state.page = option.split()[1]
+sidebar_footer()
+
+# Render the content based on the selected page
+if st.session_state.page == "Home":
+    st.markdown("<h1 style='text-align: center;'>Medical Waste Detection and Classification</h1>", unsafe_allow_html=True)
+    st.write("<p style='text-align:center; font-family:Charmonman'><b>Empowering Health, Protecting Tomorrow: Innovating Medical Waste Detection and Classification</b></p>", unsafe_allow_html=True)
+    st.image(r"im1 (1).jpg", use_column_width=True)
+    st.write("<p style='text-align:justify'>Efficient detection and careful sorting of medical waste are crucial for protecting healthcare workers, patients, and the environment. That's why we are making a system that detects different types of medical waste, such as bandages, syringes, saline bottles, cardboard, pill packets, gloves, masks, and PPE kits, and classifies them according to their particular type, such as infectious waste, pharmaceutical waste, and non-hazardous waste. This ensures that each type of waste is sorted carefully, reducing the risk of contamination and ensuring compliance with regulations. Strong detection and sorting systems not only prevent health and environmental risks but also show a commitment to responsible medical waste management.</p>", unsafe_allow_html=True)
+
+elif st.session_state.page == "Problem":
+    st.title("Problem Statement")
+    st.write("<p style='text-align:justify'>Inadequate knowledge about medical waste types and management often leads people to dispose of their waste improperly, resulting in mixed garbage that poses challenges for waste collectors during sorting, especially when dealing with hazardous materials.</p>", unsafe_allow_html=True)
+    st.image(r"prob (1).gif",use_column_width=True)
+    st.write("<p style='text-align:justify'>Our solution aims to address this issue by encouraging individuals to segregate their waste according to predefined classifications at the source. Our system facilitates waste classification, providing assistance to individuals who may not be familiar with waste types, thereby promoting proper waste management practices.</p>", unsafe_allow_html=True)
+
+
+elif st.session_state.page == "Working":
+    st.title("System Overview")
+    st.write("<p style='text-align:justify'>The outlined process describes a robust system for medical waste detection and classification, ensuring the efficient and safe management of medical waste.</p>", unsafe_allow_html=True)
+    st.image(r"Pastel (1).gif")
+    st.write("<p style='text-align:justify'>The process of medical waste detection and classification initiates with the Input stage, where an image is acquired either through a camera capture or by uploading an existing image file. Once the image is acquired, it proceeds to the Upload phase, where it is transmitted to the system for further analysis. Upon reaching the Detect Image stage, the YOLOv8 object detection algorithm is deployed. YOLOv8 meticulously scrutinizes the image, identifying various objects present within it.</p>", unsafe_allow_html=True)
+    st.write("<p style='text-align:justify'>Upon detection, the system classifies these items into four distinct categories: Infectious, Pharmaceutical, Sharps, and Non-Hazardous waste. Specifically:.</p>", unsafe_allow_html=True)
+
+    # List of items
+    items = [
+        "Gloves are classified as Infectious waste.",
+        "Pill Packets fall under the Pharmaceutical category.",
+        "Masks are categorized as Infectious waste.",
+        "Syringes are identified as Sharps.",
+        "Saline Bottles are classified as Non-Hazardous waste.",
+        "PPE Kits are categorized as Infectious waste.",
+        "Bandages are classified as Infectious waste.",
+        "Cardboard is identified as Non-Hazardous waste."
+    ]
+
+    # Create an unordered list
+    st.write("<ul>", unsafe_allow_html=True)
+
+    # Add list items
+    for item in items:
+        st.write(f"<li>{item}</li>", unsafe_allow_html=True)
+
+    # Close the unordered list
+    st.write("</ul>", unsafe_allow_html=True)
+
+    st.write("<p style='text-align:justify'>This classification enables proper handling, disposal, or treatment based on the hazard level and type of medical waste identified from the input image. By accurately detecting and sorting various types of waste materials using YOLOv8, the system facilitates the efficient and safe management of medical waste, ultimately contributing to improved healthcare waste management practices.</p>", unsafe_allow_html=True)
+
+elif st.session_state.page == "Classification":
+    st.markdown("<h1 style='text-align: center;'>Medical Waste Detection and Classification</h1>", unsafe_allow_html=True)
+    st.image(r"videocon-unscreen (1).gif", use_column_width=True)
+
+    # Streamlit app section for capturing photo and making predictions
+    st.markdown("<h4 style='text-align: center;'>Take a Picture for Prediction</h4>", unsafe_allow_html=True)
+    st.write(" ➜ Take Picture")
+    take_photo_and_classify()
+
+
+    # Streamlit app section for uploading an image and making predictions
+    st.markdown("<h4 style='text-align: center;'>Upload an Image for Prediction</h4>", unsafe_allow_html=True)
+    st.write(" ➜ Select Your Image")
+    uploaded_file = st.file_uploader("Choose a file", type=["jpg", "jpeg", "png"])
+
+    if uploaded_file is not None:
+        # Save the uploaded file
+        image_path = 'uploaded_image.jpg'
+        with open(image_path, 'wb') as f:
+            f.write(uploaded_file.getvalue())
+
+        st.success('File uploaded and saved to {}'.format(image_path))
+
+        # Read the uploaded file as bytes
+        image_bytes = uploaded_file.read()
+
+        # Make prediction
+        image, predicted_item_class, predicted_category = make_predictions(image_bytes)
+
+        # Display the prediction
+        st.subheader('Prediction:')
+        st.write('Predicted Waste Item Class:', predicted_item_class)
+        st.write('Predicted Waste Category:', predicted_category)
+
+        # Display the uploaded image
+        st.subheader('Uploaded Image:')
+        st.image(image)
+
+elif st.session_state.page == "About":
+    st.title("About Us")
+
+    st.write("<p style='text-align:justify'>We are a team of enthusiastic students from JSPM's Rajarshi Shahu College of Engineering, Pune, pursuing our Bachelor of Technology (B.Tech) in Information Technology. Passionate about technology and innovation, we come together to explore and create solutions that make a positive impact on the world around us.</p>", unsafe_allow_html=True)
+    st.write(" ")
+    # Set up a single-column layout for the first row
+    col1, col2, col3 = st.columns(3)
+
+    # Your photo and name
+    with col1:
+     st.image(r"RBTL21IT010.jpg", use_column_width=True)
+     st.write("<p style='text-align:center'>Omkar Bhalerao <br><a href='mailto:omkarbhalerao2002@gmail.com'>omkarbhalerao2002@gmail.com</a></p>", unsafe_allow_html=True)
+
+# Group member 1 photo and name
+    with col2:
+     st.image(r"Srushti.jpg", use_column_width=True)
+     st.write("<p style='text-align:center'>Srushti Bobe<br><a href='mailto:bobesrushti9146@gmail.com'>bobesrushti9146@gmail.com</a></p>", unsafe_allow_html=True)
+
+# Group member 2 photo and name
+    with col3:
+     st.image(r"Priyanka.jpg", use_column_width=True)
+     st.write("<p style='text-align:center'>Priyanka Adhav <br><a href='mailto:adhavpriyanka44@gmail.com'>adhavpriyanka44@gmail.com</a></p>", unsafe_allow_html=True)
+     st.write(" ")
+
+
+    st.write("<p style='text-align:justify'>As students of Rajarshi Shahu College of Engineering, we have access to state-of-the-art facilities and a dynamic learning environment that encourages innovation and collaboration. Our diverse backgrounds and experiences enrich our projects and enable us to approach problems from different perspectives.</p>", unsafe_allow_html=True)
+
+    st.write("Please contact us for more information.")

best.pt

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+oid sha256:a6e026dcb8d062f9797988f47ecafc9f7c036dcb227786c74417e641320020bb
+size 31698841

requirements.txt

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+altair==5.3.0
+attrs==23.2.0
+blinker==1.8.2
+cachetools==5.3.3
+certifi==2024.2.2
+charset-normalizer==3.3.2
+click==8.1.7
+colorama==0.4.6
+contourpy==1.2.1
+cycler==0.12.1
+filelock==3.14.0
+fonttools==4.52.4
+fsspec==2024.5.0
+gitdb==4.0.11
+GitPython==3.1.43
+idna==3.7
+importlib_resources==6.4.0
+intel-openmp==2021.4.0
+Jinja2==3.1.4
+jsonschema==4.22.0
+jsonschema-specifications==2023.12.1
+kiwisolver==1.4.5
+markdown-it-py==3.0.0
+MarkupSafe==2.1.5
+matplotlib==3.9.0
+mdurl==0.1.2
+mkl==2021.4.0
+mpmath==1.3.0
+networkx==3.2.1
+numpy==1.26.4
+opencv-python==4.9.0.80
+packaging==24.0
+pandas==2.2.2
+pillow==10.3.0
+protobuf==4.25.3
+psutil==5.9.8
+py-cpuinfo==9.0.0
+pyarrow==16.1.0
+pydeck==0.9.1
+Pygments==2.18.0
+pyparsing==3.1.2
+python-dateutil==2.9.0.post0
+pytz==2024.1
+PyYAML==6.0.1
+referencing==0.35.1
+requests==2.32.2
+rich==13.7.1
+rpds-py==0.18.1
+scipy==1.13.1
+seaborn==0.13.2
+six==1.16.0
+smmap==5.0.1
+streamlit==1.35.0
+sympy==1.12
+tbb==2021.12.0
+tenacity==8.3.0
+thop==0.1.1.post2209072238
+toml==0.10.2
+toolz==0.12.1
+torch==2.3.0
+torchvision==0.18.0
+tornado==6.4
+tqdm==4.66.4
+typing_extensions==4.12.0
+tzdata==2024.1
+ultralytics==8.2.23
+urllib3==2.2.1
+watchdog==4.0.1
+zipp==3.19.0

yolov8m-cls.pt

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yolov8n.pt

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