Update app.py

app.py

@@ -195,6 +195,9 @@ if not master_image_list:
 # #############################################################################
 # ############# 函数修改点：get_next_trial_info ################################
 # #############################################################################
+# #############################################################################
+# ############# 函数修改点：get_next_trial_info ################################
+# #############################################################################
 def get_next_trial_info(current_trial_idx_in_run, current_run_image_list_for_trial, num_trials_in_this_run_for_trial):
     global TARGET_DIR, METHOD_ROOTS, SUBJECTS, SENTINEL_TRIAL_INTERVAL
     global global_shown_pairs_cache, global_history_has_unsaved_changes, exhausted_target_images
@@ -206,10 +209,13 @@ def get_next_trial_info(current_trial_idx_in_run, current_run_image_list_for_tri
     target_full_path = os.path.join(TARGET_DIR, img_filename_original)
     trial_number_for_display = current_trial_idx_in_run + 1
 
-    # ---- MODIFICATION START: Create two separate pools for candidates ----
-    pool_generated_color = []
-    pool_other_methods = []
+    # ---- MODIFICATION START: 创建两个用于特定方法对比的候选池 ----
+    pool_image_flited = []
+    pool_reconed_image_color = []
     
+    # 这个独立的池用于“哨兵试验”，它需要从“任何”方法中随机抽取一个候选图
+    combined_pool_for_sentinel = []
+
     for m_root_path in METHOD_ROOTS:
         method_name = os.path.basename(m_root_path)
         
@@ -228,12 +234,15 @@ def get_next_trial_info(current_trial_idx_in_run, current_run_image_list_for_tri
                 internal_label = f"{method_name}/{s_id}/{reconstructed_filename}"
                 candidate_tuple = (internal_label, candidate_path)
                 
-                # Segregate candidates into the two pools
+                # 为常规试验，将候选图放入对应的特定池中
                 if method_name == "image_flited":
-                    pool_generated_color.append(candidate_tuple)
-                else:
-                    pool_other_methods.append(candidate_tuple)
-    # ---- MODIFICATION END: Candidate pools are now populated ----
+                    pool_image_flited.append(candidate_tuple)
+                elif method_name == "reconed_image_color":
+                    pool_reconed_image_color.append(candidate_tuple)
+
+                # 将“所有”有效的候选图都添加到哨兵池中
+                combined_pool_for_sentinel.append(candidate_tuple)
+    # ---- MODIFICATION END: 候选池已填充完毕 ----
 
     trial_info = {"image_id": img_filename_original, "target_path": target_full_path, "cur_no": trial_number_for_display, "is_sentinel": False,
                   "left_display_label": "N/A", "left_internal_label": "N/A", "left_path": None,
@@ -242,15 +251,14 @@ def get_next_trial_info(current_trial_idx_in_run, current_run_image_list_for_tri
     is_potential_sentinel_trial = (trial_number_for_display > 0 and trial_number_for_display % SENTINEL_TRIAL_INTERVAL == 0)
 
     if is_potential_sentinel_trial:
-        # For sentinel trials, we just need one random reconstruction. Combine pools to pick one.
-        combined_pool = pool_generated_color + pool_other_methods
-        if not combined_pool:
+        # 对于哨兵试验，我们从包含所有方法候选图的池中随机选择一个
+        if not combined_pool_for_sentinel:
             print(f"警告：哨兵图 '{img_filename_original}' (trial {trial_number_for_display}) 无任何候选图。")
         else:
             print(f"生成哨兵试验 for '{img_filename_original}' (trial {trial_number_for_display})")
             trial_info["is_sentinel"] = True
             sentinel_candidate_target_tuple = ("目标图像", target_full_path)
-            random_reconstruction_candidate_tuple = random.choice(combined_pool)
+            random_reconstruction_candidate_tuple = random.choice(combined_pool_for_sentinel)
             candidates_for_sentinel = [
                 (("目标图像", target_full_path), sentinel_candidate_target_tuple[0]),
                 (("重建图", random_reconstruction_candidate_tuple[1]), random_reconstruction_candidate_tuple[0])
@@ -261,22 +269,22 @@ def get_next_trial_info(current_trial_idx_in_run, current_run_image_list_for_tri
                 "right_display_label": candidates_for_sentinel[1][0][0], "right_path": candidates_for_sentinel[1][0][1], "right_internal_label": candidates_for_sentinel[1][1],
             })
     else: # 常规试验
-        # ---- MODIFICATION START: New check and pairing logic ----
-        # Check if both pools have at least one candidate
-        if not pool_generated_color or not pool_other_methods:
-            print(f"警告：常规图 '{img_filename_original}' (trial {trial_number_for_display}) 候选不足以形成指定对。 "
-                  f"('generated_images_color' 找到 {len(pool_generated_color)} 个, "
-                  f"其他��法找到 {len(pool_other_methods)} 个)。此试验无法进行。")
+        # ---- MODIFICATION START: 新的检查与配对逻辑 ----
+        # 检查两个特定的池是否都有候选图
+        if not pool_image_flited or not pool_reconed_image_color:
+            print(f"警告：常规图 '{img_filename_original}' (trial {trial_number_for_display}) 候选不足以形成 'image_flited' vs 'reconed_image_color' 对。 "
+                  f"('image_flited' 找到 {len(pool_image_flited)} 个, "
+                  f"'reconed_image_color' 找到 {len(pool_reconed_image_color)} 个)。此试验无法进行。")
             return None, current_trial_idx_in_run
 
         target_global_history_set = global_shown_pairs_cache.setdefault(img_filename_original, set())
         
-        # Generate all pairs by picking one from each pool
+        # 从两个特定池中各选一个，生成所有可能的配对
         all_possible_pairs_in_pool = []
-        for c_color, c_other in product(pool_generated_color, pool_other_methods):
-            pair_labels_fset = frozenset({c_color[0], c_other[0]})
-            all_possible_pairs_in_pool.append( ((c_color, c_other), pair_labels_fset) )
-        # ---- MODIFICATION END: New pairing logic is complete ----
+        for c_flited, c_reconed in product(pool_image_flited, pool_reconed_image_color):
+            pair_labels_fset = frozenset({c_flited[0], c_reconed[0]})
+            all_possible_pairs_in_pool.append( ((c_flited, c_reconed), pair_labels_fset) )
+        # ---- MODIFICATION END: 新的配对逻辑已完成 ----
 
         unseen_globally_pairs_with_data = [
             item for item in all_possible_pairs_in_pool if item[1] not in target_global_history_set
@@ -290,7 +298,7 @@ def get_next_trial_info(current_trial_idx_in_run, current_run_image_list_for_tri
             target_global_history_set.add(chosen_pair_frozenset)
             global_history_has_unsaved_changes = True
         else:
-            print(f"警告：目标图 '{img_filename_original}' (trial {trial_number_for_display}): 所有 ({len(all_possible_pairs_in_pool)}) 个 'generated_color' vs 'other' 对均已在全局展示过。")
+            print(f"警告：目标图 '{img_filename_original}' (trial {trial_number_for_display}): 所有 ({len(all_possible_pairs_in_pool)}) 个 'image_flited' vs 'reconed_image_color' 对均已在全局展示过。")
             if all_possible_pairs_in_pool:
                 print(f"目标图 '{img_filename_original}' 将被标记为已耗尽，未来轮次中将被跳过。")
                 exhausted_target_images.add(img_filename_original)
@@ -305,6 +313,7 @@ def get_next_trial_info(current_trial_idx_in_run, current_run_image_list_for_tri
         })
     return trial_info, current_trial_idx_in_run + 1
 
+
 # ==== 批量保存用户选择日志函数 (保持不变) ====
 def save_single_log_to_hf_dataset(log_entry, user_identifier_str):
     global DATASET_REPO_ID, INDIVIDUAL_LOGS_FOLDER