Upload app.py

app.py

@@ -9,11 +9,12 @@ import streamlit as st
 import os
 import random
 import pandas as pd
-from PIL import Image
+from PIL import Image, ImageEnhance
 import numpy as np
 import gspread
 from oauth2client.service_account import ServiceAccountCredentials
 
+
 # -------------------------
 # Global parameters
 # -------------------------
@@ -36,18 +37,23 @@ def load_image_pair(index):
 
 def form_callback(name, imgID, correct):    
     with open(RESULTS_FILE, 'a+') as f:    #Append & read mode
-        yes = f.write(f"{name},{imgID},{correct}\n")
+        f.write(f"{name},{imgID},{correct}\n")
         # st.success(f"{name},{imgID},{correct}\n")
         
-# def form_callback(name, results_list):
-#     # On convertit la liste de dictionnaires en lignes CSV.
-#     # Par exemple, on suppose que chaque dictionnaire a des clés: pair_index, pair_order, selected.
-#     with open(RESULTS_FILE, 'a+', encoding='utf-8') as f:
-#         for res in results_list:
-#             # Vous pouvez ajuster le format de la ligne en fonction de vos besoins
-#             line = f"{name},{res['pair_index']},{res['pair_order']},{res['selected']}\n"
-#             f.write(line)
-#     st.success("Results appended successfully!")
+        
+
+def match_brightness(source_img, target_img):
+    source_brightness = np.mean(np.array(source_img))
+    target_brightness = np.mean(np.array(target_img))
+
+    if target_brightness == 0:
+        factor = 1  # avoid division by zero
+    else:
+        factor = source_brightness / target_brightness
+
+    enhancer = ImageEnhance.Brightness(target_img)
+    adjusted = enhancer.enhance(factor)
+    return adjusted
 
 # -------------------------
 # Navigation via st.session_state
@@ -170,6 +176,7 @@ if st.session_state.page == "evaluation":
     img2 = Image.open(pair[1][1])
     img2 = img2.convert("L")
     
+    img2 = match_brightness(img1, img2)
     
     # Affichage dans deux colonnes avec radio buttons sous chacune
     col1, col2 = st.columns(2)