Update app.py

app.py

@@ -4,15 +4,8 @@ import pandas as pd
 import torch
 from PIL import Image
 import numpy as np
-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
+from main import predict_caption, CLIPModel , get_text_embeddings
 
-openai.api_key = "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"
 
 st.markdown(
     """
@@ -20,35 +13,12 @@ st.markdown(
     body {
         background-color: transparent;
     }
-    .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")
@@ -56,85 +26,26 @@ model = CLIPModel().to(device)
 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, top_k=1):
+def show_predicted_caption(image):
     matches = predict_caption(
         image, model, text_embeddings, testing_df["caption"]
-    )[: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
-
+    )[0]
+    return matches
 
-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("Medical Image Captioning")
+st.write("Upload an image to get a caption:")
 
-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 Report"):
-        with st.spinner("Generating Report..."):
+    if st.button("Generate Caption"):
+        with st.spinner("Generating caption..."):
             image_np = np.array(image)
-            caption = show_predicted_caption(image_np)[0]
-
+            caption = show_predicted_caption(image_np)
             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)
+