Update app.py

app.py

@@ -3,7 +3,7 @@ import tifffile
 import pydicom
 from scipy.ndimage import zoom
 import torch
-#from core.models.dani_model import dani_model
+from core.models.dani_model import dani_model
 import numpy as np
 from PIL import Image
 import base64
@@ -20,18 +20,18 @@ device = torch.device('cuda' if torch.cuda.is_available() else 'cpu')
 
 # Dati di esempio predefiniti
 esempi = {
-    "FRO -> LAT": {'FRO': 'FtoL.png', 'LAT': 'LfromF.png'},
-    "FRO -> REP": {'FRO': '31d9847f-987fcf63-704f7496-d2b21eb8-63cd973e.tiff', 'REP': 'Small bilateral pleural effusions, left greater than right.'},
-    "FRO -> LAT + REP": {'FRO': '81bca127-0c416084-67f8033c-ecb26476-6d1ecf60.tiff', 'LAT': 'd52a0c5c-bb7104b0-b1d821a5-959984c3-33c04ccb.tiff', 'REP': 'No acute intrathoracic process. Heart Size is normal. Lungs are clear. No pneumothorax'},
-    "LAT -> FRO": {'LAT': 'LtoF.png', 'FRO': 'FfromL.png'},
-    "LAT -> REP": {'LAT': 'd52a0c5c-bb7104b0-b1d821a5-959984c3-33c04ccb.tiff', 'REP': 'no acute cardiopulmonary process. if concern for injury persists, a dedicated rib series with markers would be necessary to ensure no rib fractures.'},
-    "LAT -> FRO + REP": {'LAT': 'reald52a0c5c-bb7104b0-b1d821a5-959984c3-33c04ccb.tiff', 'FRO': 'ab37274f-b4c1fc04-e2ff24b4-4a130ba3-cd167968.tiff', 'REP': 'No acute intrathoracic process. If there is strong concern for rib fracture, a dedicated rib series may be performed.'},
-    "REP -> FRO": {'REP': 'Left lung opacification which may reflect pneumonia superimposed on metastatic disease.', 'FRO': '02aa804e-bde0afdd-112c0b34-7bc16630-4e384014.tiff'},
-    "REP -> LAT": {'REP': 'Bilateral pleural effusions, cardiomegaly and mild edema suggest fluid overload.', 'LAT': '489faba7-a9dc5f1d-fd7241d6-9638d855-eaa952b1.tiff'},
-    "REP -> FRO + LAT": {'REP': 'No acute intrathoracic process. The lungs are clean and heart is normal size.', 'FRO': 'f27ba7cd-44486c2e-29f3e890-f2b9f94e-84110448.tiff', 'LAT': 'b20c9570-de77944a-b8604ba0-73305a7b-d608a72b.tiff'},
-    "FRO + LAT -> REP": {'FRO': '95856dd1-5878b5b1-9c104817-760c0122-6187946f.tiff', 'LAT': '3723d912-71940d69-4fef2dd2-27af5a7b-127ba20c.tiff', 'REP': 'Opacities in the right upper or middle lobe, maybe early pneumonia.'},
-    "FRO + REP -> LAT": {'FRO': 'e7f21453-7956d79a-44e44614-fae8ff16-d174d1a0.tiff', 'REP': 'No focal consolidation.', 'LAT': '8037e6b9-06367464-a4ccd63a-5c5c5a81-ce3e7ffc.tiff'},
-    "LAT + REP -> FRO": {'LAT': '02c66644-b1883a91-54aed0e7-62d25460-398f9865.tiff', 'REP': 'No evidence of acute cardiopulmonary process.', 'FRO': 'b1f169f1-12177dd5-2fa1c4b1-7b816311-85d769e9.tiff'}
+    "Frontal -> Lateral": {'Frontal': 'FtoL.png', 'Lateral': 'LfromF.png'},
+    "Frontal -> Report": {'Frontal': '31d9847f-987fcf63-704f7496-d2b21eb8-63cd973e.tiff', 'Report': 'Small bilateral pleural effusions, left greater than right.'},
+    "Frontal -> Lateral + Report": {'Frontal': '81bca127-0c416084-67f8033c-ecb26476-6d1ecf60.tiff', 'Lateral': 'd52a0c5c-bb7104b0-b1d821a5-959984c3-33c04ccb.tiff', 'Report': 'No acute intrathoracic process. Heart Size is normal. Lungs are clear. No pneumothorax'},
+    "Lateral -> Frontal": {'Lateral': 'LtoF.png', 'Frontal': 'FfromL.png'},
+    "Lateral -> Report": {'Lateral': 'd52a0c5c-bb7104b0-b1d821a5-959984c3-33c04ccb.tiff', 'Report': 'no acute cardiopulmonary process. if concern for injury persists, a dedicated rib series with markers would be necessary to ensure no rib fractures.'},
+    "Lateral -> Frontal + Report": {'Lateral': 'reald52a0c5c-bb7104b0-b1d821a5-959984c3-33c04ccb.tiff', 'Frontal': 'ab37274f-b4c1fc04-e2ff24b4-4a130ba3-cd167968.tiff', 'Report': 'No acute intrathoracic process. If there is strong concern for rib fracture, a dedicated rib series may be performed.'},
+    "Report -> Frontal": {'Report': 'Left lung opacification which may reflect pneumonia superimposed on metastatic disease.', 'Frontal': '02aa804e-bde0afdd-112c0b34-7bc16630-4e384014.tiff'},
+    "Report -> Lateral": {'Report': 'Bilateral pleural effusions, cardiomegaly and mild edema suggest fluid overload.', 'Lateral': '489faba7-a9dc5f1d-fd7241d6-9638d855-eaa952b1.tiff'},
+    "Report -> Frontal + Lateral": {'Report': 'No acute intrathoracic process. The lungs are clean and heart is normal size.', 'Frontal': 'f27ba7cd-44486c2e-29f3e890-f2b9f94e-84110448.tiff', 'Lateral': 'b20c9570-de77944a-b8604ba0-73305a7b-d608a72b.tiff'},
+    "Frontal + Lateral -> Report": {'Frontal': '95856dd1-5878b5b1-9c104817-760c0122-6187946f.tiff', 'Lateral': '3723d912-71940d69-4fef2dd2-27af5a7b-127ba20c.tiff', 'Report': 'Opacities in the right upper or middle lobe, maybe early pneumonia.'},
+    "Frontal + Report -> Lateral": {'Frontal': 'e7f21453-7956d79a-44e44614-fae8ff16-d174d1a0.tiff', 'Report': 'No focal consolidation.', 'Lateral': '8037e6b9-06367464-a4ccd63a-5c5c5a81-ce3e7ffc.tiff'},
+    "Lateral + Report -> Frontal": {'Lateral': '02c66644-b1883a91-54aed0e7-62d25460-398f9865.tiff', 'Report': 'No evidence of acute cardiopulmonary process.', 'Frontal': 'b1f169f1-12177dd5-2fa1c4b1-7b816311-85d769e9.tiff'}
 }
 
 
@@ -130,7 +130,7 @@ if st.session_state['step'] == 1:
     # Breve descrizione del lavoro
     st.markdown("""
         <div style='text-align: justify; font-size: 18px; line-height: 1.6;'>
-            This work introduces MedCoDi-M, a novel multi-prompt vision-language model for multi-modal medical data generation. 
+            This work introduces MedCoDi-M, a novel multi-prompt foundation model for multi-modal medical data generation. 
             In this demo, you will be able to perform various generation tasks including frontal and lateral chest X-rays and clinical report generation.
             MedCoDi-M enables flexible, any-to-any generation across different medical data modalities, utilizing contrastive learning and a modular approach for enhanced performance.
         </div>
@@ -141,7 +141,7 @@ if st.session_state['step'] == 1:
 
     # Immagine con didascalia migliorata e con dimensione della caption aumentata
     image_path = "./DEMO/Loghi/model_final.png"  # Sostituisci con il percorso della tua immagine
-    st.image(image_path, caption='', use_column_width=True)
+    st.image(image_path, caption='', use_container_width=True)
 
     # Caption con dimensione del testo migliorata
     st.markdown("""
@@ -163,15 +163,15 @@ if st.session_state['step'] == 1:
 if st.session_state['step'] == 2:
     # Opzioni disponibili
     options = [
-        "FRO -> LAT", "FRO -> REP", "FRO -> LAT + REP",
-        "LAT -> FRO", "LAT -> REP", "LAT -> FRO + REP",
-        "REP -> FRO", "REP -> LAT", "REP -> FRO + LAT",
-        "FRO + LAT -> REP", "FRO + REP -> LAT", "LAT + REP -> FRO"
+        "Frontal -> Lateral", "Frontal -> Report", "Frontal -> Lateral + Report",
+        "Lateral -> Frontal", "Lateral -> Report", "Lateral -> Frontal + Report",
+        "Report -> Frontal", "Report -> Lateral", "Report -> Frontal + Lateral",
+        "Frontal + Lateral -> Report", "Frontal + Report -> Lateral", "Lateral + Report -> Frontal"
     ]
 
     # Messaggio di selezione con dimensione aumentata
     st.markdown(
-        "<h4 style='text-align: justify'><strong>Select the type of generation you want to perform: (FRO = Frontal, LAT = Lateral, REP = Report)</strong></h4>",
+        "<h4 style='text-align: justify'><strong>Select the type of generation you want to perform:</strong></h4>",
         unsafe_allow_html=True)
 
     # Aumentare la dimensione di "Please select an option:"
@@ -220,17 +220,17 @@ if st.session_state['step'] == 3:
         unsafe_allow_html=True)
 
     # Carica l'immagine frontale
-    if "FRO" in st.session_state['selected_option'].split(" ->")[0]:
+    if "Frontal" in st.session_state['selected_option'].split(" ->")[0]:
         st.markdown("<h5 style='font-size: 18px;'>Load the Frontal X-ray in DICOM format</h5>", unsafe_allow_html=True)
         st.session_state['frontal_file'] = st.file_uploader("", type=["dcm"])
 
     # Carica l'immagine laterale
-    if "LAT" in st.session_state['selected_option'].split(" ->")[0]:
+    if "Lateral" in st.session_state['selected_option'].split(" ->")[0]:
         st.markdown("<h5 style='font-size: 18px;'>Load the Lateral X-ray in DICOM format</h5>", unsafe_allow_html=True)
         st.session_state['lateral_file'] = st.file_uploader("", type=["dcm"])
 
     # Inserisci il report clinico
-    if "REP" in st.session_state['selected_option'].split(" ->")[0]:
+    if "Report" in st.session_state['selected_option'].split(" ->")[0]:
         st.markdown("<h5 style='font-size: 18px;'>Type the clinical report</h5>", unsafe_allow_html=True)
         st.session_state['report'] = st.text_area("", value=st.session_state['report'])
 
@@ -249,11 +249,11 @@ if st.session_state['step'] == 3:
             with st.spinner("Preprocessing the data..."):
                 time.sleep(3)
             # Controllo che i file necessari siano stati caricati
-            if "FRO" in st.session_state['selected_option'].split(" ->")[0] and not st.session_state['frontal_file']:
+            if "Frontal" in st.session_state['selected_option'].split(" ->")[0] and not st.session_state['frontal_file']:
                 st.error("Load the Frontal image.")
-            elif "LAT" in st.session_state['selected_option'].split(" ->")[0] and not st.session_state['lateral_file']:
+            elif "Lateral" in st.session_state['selected_option'].split(" ->")[0] and not st.session_state['lateral_file']:
                 st.error("Load the Lateral image.")
-            elif "REP" in st.session_state['selected_option'].split(" ->")[0] and not st.session_state['report']:
+            elif "Report" in st.session_state['selected_option'].split(" ->")[0] and not st.session_state['report']:
                 st.error("Type the clinical report.")
             else:
                 st.write(f"Execution of: {st.session_state['selected_option']}")
@@ -311,7 +311,7 @@ if st.session_state['step'] == 3:
                     if lateral.dtype != np.uint8:
                         lateral2 = (255 * (lateral - lateral.min()) / (lateral.max() - lateral.min())).astype(np.uint8)
                     lateral = torch.tensor(lateral, dtype=torch.float32).unsqueeze(0).unsqueeze(0)
-                    lateral2 = Image.fromarray(lateral2)
+                    lateral2 = Image.Frontalmarray(lateral2)
                     st.write("Lateral Image loaded successfully!")
                     st.image(lateral2, caption="Lateral Image Loaded", use_column_width=True)
                 if st.session_state['report']:
@@ -319,20 +319,20 @@ if st.session_state['step'] == 3:
                     st.write(f"Loaded Report: {report}")
 
                 inputs = []
-                if "FRO" in st.session_state['selected_option'].split(" ->")[0]:
+                if "Frontal" in st.session_state['selected_option'].split(" ->")[0]:
                     inputs.append('frontal')
-                if "LAT" in st.session_state['selected_option'].split(" ->")[0]:
+                if "Lateral" in st.session_state['selected_option'].split(" ->")[0]:
                     inputs.append('lateral')
-                if "REP" in st.session_state['selected_option'].split(" ->")[0]:
+                if "Report" in st.session_state['selected_option'].split(" ->")[0]:
                     inputs.append('text')
 
                 # Ora vediamo cosa c'è dopo la freccia
                 outputs = []
-                if "FRO" in st.session_state['selected_option'].split(" ->")[1]:
+                if "Frontal" in st.session_state['selected_option'].split(" ->")[1]:
                     outputs.append('frontal')
-                if "LAT" in st.session_state['selected_option'].split(" ->")[1]:
+                if "Lateral" in st.session_state['selected_option'].split(" ->")[1]:
                     outputs.append('lateral')
-                if "REP" in st.session_state['selected_option'].split(" ->")[1]:
+                if "Report" in st.session_state['selected_option'].split(" ->")[1]:
                     outputs.append('text')
 
                 # Ultima cosa che va fatta è passare allo step 4, prima di farlo però, tutte le variabili che ci servono
@@ -383,20 +383,20 @@ if st.session_state['step'] == 5:
         unsafe_allow_html=True)
 
     inputs = []
-    if "FRO" in st.session_state['selected_option'].split(" ->")[0]:
-        inputs.append('FRO')
-    if "LAT" in st.session_state['selected_option'].split(" ->")[0]:
-        inputs.append('LAT')
-    if "REP" in st.session_state['selected_option'].split(" ->")[0]:
-        inputs.append('REP')
+    if "Frontal" in st.session_state['selected_option'].split(" ->")[0]:
+        inputs.append('Frontal')
+    if "Lateral" in st.session_state['selected_option'].split(" ->")[0]:
+        inputs.append('Lateral')
+    if "Report" in st.session_state['selected_option'].split(" ->")[0]:
+        inputs.append('Report')
 
     outputs = []
-    if "FRO" in st.session_state['selected_option'].split(" ->")[1]:
-        outputs.append('FRO')
-    if "LAT" in st.session_state['selected_option'].split(" ->")[1]:
-        outputs.append('LAT')
-    if "REP" in st.session_state['selected_option'].split(" ->")[1]:
-        outputs.append('REP')
+    if "Frontal" in st.session_state['selected_option'].split(" ->")[1]:
+        outputs.append('Frontal')
+    if "Lateral" in st.session_state['selected_option'].split(" ->")[1]:
+        outputs.append('Lateral')
+    if "Report" in st.session_state['selected_option'].split(" ->")[1]:
+        outputs.append('Report')
 
     esempio = esempi[st.session_state['selected_option']]
 
@@ -410,8 +410,8 @@ if st.session_state['step'] == 5:
 
     for idx, inp in enumerate(inputs):
         with input_cols[idx]:
-            if inp == 'FRO':
-                path = "./DEMO/ESEMPI/" + esempio['FRO']
+            if inp == 'Frontal':
+                path = "./DEMO/ESEMPI/" + esempio['Frontal']
                 print(path)
                 if path.endswith(".tiff"):
                     im = tifffile.imread(path)
@@ -419,16 +419,16 @@ if st.session_state['step'] == 5:
                 elif path.endswith(".png"):
                     im = Image.open(path)
                 st.image(im, caption="Frontal Image")
-            elif inp == 'LAT':
-                path = "./DEMO/ESEMPI/" + esempio['LAT']
+            elif inp == 'Lateral':
+                path = "./DEMO/ESEMPI/" + esempio['Lateral']
                 if path.endswith(".tiff"):
                     im = tifffile.imread(path)
                     im = np.clip(im, 0, 1)
                 elif path.endswith(".png"):
                     im = Image.open(path)
                 st.image(im, caption="Lateral Image")
-            elif inp == 'REP':
-                st.write(f"Report: {esempio['REP']}")
+            elif inp == 'Report':
+                st.write(f"Report: {esempio['Report']}")
 
     st.markdown(
         "<h3 style='text-align: justify'><strong>OUTPUTS</strong></h3>",
@@ -439,8 +439,8 @@ if st.session_state['step'] == 5:
 
     for idx, out in enumerate(outputs):
         with output_cols[idx]:
-            if out == 'FRO':
-                path = "./DEMO/ESEMPI/" + esempio['FRO']
+            if out == 'Frontal':
+                path = "./DEMO/ESEMPI/" + esempio['Frontal']
                 if path.endswith(".tiff"):
                     im = tifffile.imread(path)
                     # facciamo clamp tra 0 e 1
@@ -448,8 +448,8 @@ if st.session_state['step'] == 5:
                 elif path.endswith(".png"):
                     im = Image.open(path)
                 st.image(im, caption="Frontal Image")
-            elif out == 'LAT':
-                path = "./DEMO/ESEMPI/" + esempio['LAT']
+            elif out == 'Lateral':
+                path = "./DEMO/ESEMPI/" + esempio['Lateral']
                 if path.endswith(".tiff"):
                     im = tifffile.imread(path)
                     # facciamo clamp tra 0 e 1
@@ -457,8 +457,8 @@ if st.session_state['step'] == 5:
                 elif path.endswith(".png"):
                     im = Image.open(path)
                 st.image(im, caption="Lateral Image")
-            elif out == 'REP':
-                st.write(f"Report: {esempio['REP']}")
+            elif out == 'Report':
+                st.write(f"Report: {esempio['Report']}")
 
     # Pulsante per tornare all'inizio
     if st.button("Return to the beginning"):