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import streamlit as st |
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from ultralytics import YOLO |
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import pandas as pd |
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import numpy as np |
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from io import StringIO |
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import PIL |
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from PIL import Image |
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import requests |
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from io import BytesIO |
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st.title("cancer-detection") |
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st.text("Upload image here:") |
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uploaded_file = st.file_uploader("Choose a file", type=['png', 'jpg']) |
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if uploaded_file is not None: |
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st.write("filename:", uploaded_file.name) |
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uploaded_image = PIL.Image.open(uploaded_file) |
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st.image(uploaded_image, caption='Input', width=200) |
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type_=st.selectbox("Choose any one type of detection", (('Brain'), ('Skin'))) |
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conf = st.slider('Set confidence level percentage', 0, 100, 25) |
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if type_=='Brain': |
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model= YOLO("cd_detect.pt") |
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confi=conf/100 |
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res=model(uploaded_image, conf=confi) |
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img=res[0].plot() |
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a=res[0] |
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if a.masks is not None: |
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st.image(img, caption='Output', width=600) |
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else: |
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st.write("No detections found") |
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if type_=='Skin': |
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model= YOLO("skin_detect.pt") |
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confi=conf/100 |
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res=model(uploaded_image, conf=confi) |
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img=res[0].plot() |
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a=res[0] |
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if a.masks is not None: |
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st.image(img, caption='Output', width=600) |
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else: |
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st.write("No detections found") |
