Upload app.py

app.py

@@ -15,17 +15,17 @@ import numpy as np
 # -------------------------
 # Global parameters
 # -------------------------
-IMAGE_DIR = "images"         # Dossier contenant les images
-NUM_PAIRS = 10               # Nombre total de paires à évaluer
-RESULTS_FILE = "results.csv" # Fichier CSV de sauvegarde des réponses
+IMAGE_DIR = "images"         # Folder containing images
+NUM_PAIRS = 10               # Total number of pairs to be assessed
+# RESULTS_FILE = "results.csv" # CSV file for saving responses
 
 # -------------------------
 # Helper functions
 # -------------------------
 def load_image_pair(index):
     """
-    Pour un index donné (entier), retourne le chemin du ground truth et celui de la génération.
-    Les fichiers sont nommés avec un index à 5 chiffres.
+    For a given index (integer), returns the path of the ground truth and the path of AI generated image.
+    Files are named with a 5-digit index.
     """
     idx_str = str(index).zfill(5)
     gt_path = os.path.join(IMAGE_DIR, f"{idx_str}.png")
@@ -34,17 +34,6 @@ def load_image_pair(index):
 
 
 
-# def get_shuffled_pair(index):
-#     """Charge la paire d'images et retourne une liste de tuples (label, image) dans un ordre aléatoire.
-#        Le label est 'GT' pour ground truth et 'Pred' pour generated.
-#     """
-#     gt_path, pred_path = load_image_pair(index)
-#     img_gt = open_image(gt_path)
-#     img_pred = open_image(pred_path)
-#     pair = [("GT", img_gt), ("Pred", img_pred)]
-#     random.shuffle(pair)
-#     return pair
-
 # -------------------------
 # Navigation via st.session_state
 # -------------------------
@@ -58,7 +47,8 @@ if "results" not in st.session_state:
     st.session_state.results = []
 if "list_pair" not in st.session_state:
     st.session_state.list_pair = []
-
+if "list_pair_ID" not in st.session_state:
+    st.session_state.list_pair_ID = []
 
     
     
@@ -66,14 +56,14 @@ if "list_pair" not in st.session_state:
 # Intro page
 # -------------------------
 if st.session_state.page == "intro":
-    st.title("Wood Surface Evaluation Study")
+    st.title("Wood Evaluation Study")
     st.markdown(
         """
         **Welcome!**
 
         In this study, you will be shown pairs of wood surface images.
-        One image is a real photograph (Ground Truth) and the other is generated by AI.
-        Your task is to select, by answering below each image, which one you believe is **real**.
+        One image is a real photograph and the other is generated by AI.
+        Your task is to select the image you believe is **real**.
 
         Please enter your name below and click **Start Evaluation** to begin.
         """
@@ -84,9 +74,10 @@ if st.session_state.page == "intro":
         st.session_state.page = "evaluation"
         st.rerun()
     
-    rd_ID_list = random.sample(range(1, 51), NUM_PAIRS)
+    st.session_state.list_pair_ID = random.sample(range(1, 51), NUM_PAIRS)
+    
 
-    for i, index in enumerate(rd_ID_list):
+    for i, index in enumerate(st.session_state.list_pair_ID):
         
         gt_path, pred_path = load_image_pair(index)
         
@@ -102,7 +93,7 @@ if st.session_state.page == "intro":
 # Evaluation page
 # -------------------------
 if st.session_state.page == "evaluation":
-    st.title("Wood Surface Evaluation")
+    st.title("Wood Evaluation")
     # st.write(f"User: **{st.session_state.user_name}**")
     
     # If all pairs have been evaluated, display a message and save the results
@@ -118,7 +109,7 @@ if st.session_state.page == "evaluation":
         
         st.success(f"Number of correct answers: {nb_correct}/{NUM_PAIRS}")
         
-        d = {'ID_img': rd_ID_list, 'Correct': correct_guess}
+        d = {'ID_img': st.session_state.list_pair_ID, 'Correct': correct_guess}
         df = pd.DataFrame(data=d)
         df.to_csv(st.session_state.user_name+'.csv')