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import streamlit as st
from transformers import pipeline
from PIL import Image
# Load the pre-trained image classification pipeline
pipe = pipeline("image-classification", model="ALM-AHME/convnextv2-large-1k-224-finetuned-BreastCancer-Classification-BreakHis-AH-60-20-20")
# Define the decision logic based on confidence scores
def classify_mammogram(img):
results = pipe(img)
predicted_label = results[0]['label']
confidence = results[0]['score']
if predicted_label == "malignant":
if confidence >= 0.8:
classification = "Non-suspicious"
elif 0.6 <= confidence < 0.8:
classification = "High risk"
else:
classification = "Indeterminate"
else: # Benign prediction
if confidence < 0.4:
classification = "Suspicious"
elif 0.4 <= confidence < 0.8:
classification = "Non-suspicious"
else:
classification = "No risk"
return f"Predicted Class: {predicted_label}\nClassification: {classification}\nConfidence: {confidence:.2f}"
# Streamlit app
st.title("Breast Cancer Detection App")
st.write("Upload an image of a mammogram(an X-ray image of the breast), and the model will predict whether it is benign or malignant.")
uploaded_file = st.file_uploader("Upload an image...", type=["jpg", "jpeg", "png"])
if uploaded_file is not None:
image = Image.open(uploaded_file)
st.image(image, caption='Uploaded Image.', use_column_width=True)
st.write("Classifying...")
classification_result = classify_mammogram(image)
st.write(classification_result)
st.write(
"""
<div style='display: flex; justify-content: space-between;'>
<div style='width: 48%;'>
<p style='font-size: 18px; font-weight: bold;'>Malignant</p>
<p style='font-size: 16px;'>
Definition: very virulent or infectious.
Non-suspicious: The AI is confident that no suspicious signs are present.<br>
High risk: The AI is confident that the results are highly suspicious.<br>
Indeterminate: The AI is uncertain and not confident in making a definitive classification.
</p>
</div>
<div style='width: 48%;'>
<p style='font-size: 18px; font-weight: bold;'>Benign</p>
<p style='font-size: 16px;'>
Definition: Not harmful in effect
Suspicious: AI is not that confident. Further Supervision is needed.<br>
Non-Suspicious: AI is confident that there is nothing to worry about.<br>
No Risk: AI is confident. No direct supervision is needed.
</p>
</div>
</div>
""",
unsafe_allow_html=True
)
# Educational content
st.markdown("### Learn More About Breast Cancer")
st.markdown("""
- [Breast Cancer Overview](https://www.who.int/news-room/fact-sheets/detail/breast-cancer)
- [Preventing Breast Cancer](https://www.cancer.gov/types/breast/patient/breast-prevention-pdq)
""")
# Determine the current Streamlit theme (light or dark)
theme = st.get_option("theme.base")
# Define button styling based on theme
if theme == "light":
button_bg_color = "#2c2e35"
button_border_color = "1px solid black"
button_text_color = "black"
else:
button_bg_color = "#2c2e35"
button_border_color = "1px solid #fff"
button_text_color = "#fff"
# Rounded button-like element with dynamic styling
st.markdown(f"""
<style>
.rounded-button {{
display: inline-block;
padding: 7px 15px;
font-size: 16px;
color: {button_text_color};
background-color: {button_bg_color};
border: {button_border_color};
border-radius: 7px;
text-align: center;
text-decoration: none;
cursor: default;
}}
</style>
<div style="text-align: center;">
<div class="rounded-button">
Created by: Samuel Ameyaw
</div>
</div>
""", unsafe_allow_html=True)
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