Update app.py

app.py

@@ -1,51 +1,140 @@
-import streamlit as st
-import pickle
-import pandas as pd
 import torch
 from PIL import Image
+import streamlit as st
 import numpy as np
-from main import predict_caption, CLIPModel , get_text_embeddings
+import pandas as pd
+from main import predict_caption, CLIPModel, get_text_embeddings
+import openai
+import base64
+from docx import Document
+from docx.enum.text import WD_PARAGRAPH_ALIGNMENT
+from io import BytesIO
+import re
 
+openai.api_key = "sk-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"
 
 st.markdown(
     """
-<style>
+    <style>
     body {
         background-color: transparent;
     }
-</style>
-""",
+    .container {
+        display: flex;
+        justify-content: center;
+        align-items: center;
+        background-color: rgba(255, 255, 255, 0.7);
+        border-radius: 15px;
+        padding: 20px;
+    }
+    .stApp {
+        background-color: transparent;
+    }
+    .stText, .stMarkdown, .stTextInput>label, .stButton>button>span {
+        color: #1c1c1c !important; /* Set the dark text color for text elements */
+    }
+    .stButton>button>span {
+        color: initial !important; /* Reset the text color for the 'Generate Caption' button */
+    }
+    .stMarkdown h1, .stMarkdown h2 {
+        color: #ff6b81 !important; /* Set the text color of h1 and h2 elements to soft red-pink */
+        font-weight: bold; /* Set the font weight to bold */
+        border: 2px solid #ff6b81; /* Add a bold border around the headers */
+        padding: 10px; /* Add padding to the headers */
+        border-radius: 5px; /* Add border-radius to the headers */
+    }
+    </style>
+    """,
     unsafe_allow_html=True,
 )
 
 
+
 device = torch.device("cpu")
 
 testing_df = pd.read_csv("testing_df.csv")
-model = CLIPModel().to(device)
+model = CLIPModel()  # Create an instance of CLIPModel
 model.load_state_dict(torch.load("weights.pt", map_location=torch.device('cpu')))
+# ...)
 text_embeddings = torch.load('saved_text_embeddings.pt', map_location=device)
 
+def download_link(content, filename, link_text):
+    b64 = base64.b64encode(content).decode()
+    href = f'<a href="data:application/octet-stream;base64,{b64}" download="{filename}">{link_text}</a>'
+    return href
 
-def show_predicted_caption(image):
+def show_predicted_caption(image, top_k=8):
     matches = predict_caption(
         image, model, text_embeddings, testing_df["caption"]
-    )[0]
-    return matches
+    )[:top_k]
+    cleaned_matches = [re.sub(r'\s\(ROCO_\d+\)', '', match) for match in matches]  # Add this line to clean the matches
+    return cleaned_matches  # Return the cleaned_matches instead of matches
+
+def generate_radiology_report(prompt):
+    response = openai.Completion.create(
+        engine="text-davinci-003",
+        prompt=prompt,
+        max_tokens=800,
+        n=1,
+        stop=None,
+        temperature=1,
+    )
+    report = response.choices[0].text.strip()
+    # Remove reference string from the report
+    report = re.sub(r'\(ROCO_\d+\)', '', report).strip()
+    return report
 
-st.title("Medical Image Captioning")
-st.write("Upload an image to get a caption:")
 
+def save_as_docx(text, filename):
+    document = Document()
+    document.add_paragraph(text)
+    with BytesIO() as output:
+        document.save(output)
+        output.seek(0)
+        return output.getvalue()
+
+st.title("RadiXGPT: An Evolution of machine doctors towards Radiology")
+
+
+# Collect user's personal information
+st.subheader("Personal Information")
+first_name = st.text_input("First Name")
+last_name = st.text_input("Last Name")
+age = st.number_input("Age", min_value=0, max_value=120, value=25, step=1)
+gender = st.selectbox("Gender", ["Male", "Female", "Other"])
+
+st.write("Upload Scan to get Radiological Report:")
 uploaded_file = st.file_uploader("Choose an image...", type=["jpg", "png", "jpeg"])
 if uploaded_file is not None:
     image = Image.open(uploaded_file)
-    st.image(image, caption="Uploaded Image", use_column_width=True)
-    st.write("")
-
     if st.button("Generate Caption"):
         with st.spinner("Generating caption..."):
             image_np = np.array(image)
-            caption = show_predicted_caption(image_np)
+            caption = show_predicted_caption(image_np)[0]
+
             st.success(f"Caption: {caption}")
 
-            
+            # Generate the radiology report
+            radiology_report = generate_radiology_report(f"Write Complete Radiology Report for this with clinical info, subjective, Assessment, Finding, Impressions, Conclusion and more in proper order : {caption}")
+
+            # Add personal information to the radiology report
+            radiology_report_with_personal_info = f"Patient Name: {first_name} {last_name}\nAge: {age}\nGender: {gender}\n\n{radiology_report}"
+
+            st.header("Radiology Report")
+            st.write(radiology_report_with_personal_info)
+            st.markdown(download_link(save_as_docx(radiology_report_with_personal_info, "radiology_report.docx"), "radiology_report.docx", "Download Report as DOCX"), unsafe_allow_html=True)
+
+        feedback_options = ["Satisfied", "Not Satisfied"]
+        selected_feedback = st.radio("Please provide feedback on the generated report:", feedback_options)
+
+        if selected_feedback == "Not Satisfied":
+            if st.button("Regenerate Report"):
+                with st.spinner("Regenerating report..."):
+                    alternative_caption = get_alternative_caption(image_np, model, text_embeddings, testing_df["caption"])
+                    regenerated_radiology_report = generate_radiology_report(f"Write Complete Radiology Report for this with clinical info, subjective, Assessment, Finding, Impressions, Conclusion and more in proper order : {alternative_caption}")
+
+                    regenerated_radiology_report_with_personal_info = f"Patient Name: {first_name} {last_name}\nAge: {age}\nGender: {gender}\n\n{regenerated_radiology_report}"
+
+                    st.header("Regenerated Radiology Report")
+                    st.write(regenerated_radiology_report_with_personal_info)
+                    st.markdown(download_link(save_as_docx(regenerated_radiology_report_with_personal_info, "regenerated_radiology_report.docx"), "regenerated_radiology_report.docx", "Download Regenerated Report as DOCX"), unsafe_allow_html=True)